Post on 13-Aug-2018
Copyright � 2006 by the Genetics Society of AmericaDOI: 10.1534/genetics.106.060004
Genetic and Environmental Effects on Complex Traits in Mice
William Valdar,*,1 Leah C. Solberg,† Dominique Gauguier,* William O. Cookson,*J. Nicholas P. Rawlins,‡ Richard Mott* and Jonathan Flint*
*Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, United Kingdom, †Medical College of Wisconsin, HMGC,Milwaukee, Wisconsin 53226 and ‡Department of Experimental Psychology, University of Oxford, Oxford, OX1 3UD, United Kingdom
Manuscript received April 26, 2006Accepted for publication July 23, 2006
ABSTRACT
The interaction between genotype and environment is recognized as an important source ofexperimental variation when complex traits are measured in the mouse, but the magnitude of thatinteraction has not often been measured. From a study of 2448 genetically heterogeneous mice, we reportthe heritability of 88 complex traits that include models of human disease (asthma, type 2 diabetesmellitus, obesity, and anxiety) as well as immunological, biochemical, and hematological phenotypes. Weshow that environmental and physiological covariates are involved in an unexpectedly large number ofsignificant interactions with genetic background. The 15 covariates we examined have a significant effecton behavioral and physiological tests, although they rarely explain .10% of the variation. We found thatinteraction effects are more frequent and larger than the main effects: half of the interactions explained.20% of the variance and in nine cases exceeded 50%. Our results indicate that assays of gene functionusing mouse models should take into account interactions between gene and environment.
IT is widely recognized that environmental variables,such as who carries out the experiment and when,
and physiological variables, such as sex and weight, areconfounds that need to be accounted for during thecollection of mouse phenotypes. Many articles attest tothe effect of these variables on phenotypic values (e.g.,Chesler et al. 2002a; Champy et al. 2004) and point outthe need for rigorous standardization of laboratorypractice (Henderson 1970; Crabbe et al. 1999; Brown
et al. 2005). It is also acknowledged that the size andeven direction of environmental effects on a phenotypecan vary with genotype, a phenomenon known as gene-by-environment interaction, and this has been docu-mented in studies of rodents over the past 50 years (e.g.,Cooper and Zubek 1958).
Following a report on the importance of laboratory-by-strain interaction (Crabbe et al. 1999), recent inter-est has focused on the prevalence and size of suchinteractions, as well as their ability to increase power ingenetic mapping experiments (Wang et al. 2006). Table1 summarizes the available data and shows that thepicture of how much genetic and environmental factorsinteract is piecemeal: our knowledge of the relative sizeof interaction and main effects is limited to a handful ofphenotype–covariate combinations.
During an investigation of the genetic basis of com-plex traits in 2448 genetically heterogeneous stock (HS)
mice (1220 female, 1228 male) (Solberg et al. 2006),we collected environmental and physiological covari-ates. The mice we used were descended from eightinbred strains (A/J, AKR/J, BALBc/J, CBA/J, C3H/HeJ, C57BL/6J, DBA/2J, and LP/J) (Demarest et al.2001), incorporating more genetic variation from asingle cross than has hitherto been assessed in mice.The generality of our findings is enhanced by our use ofa battery of tests that includes both behavioral and abroad range of physiological phenotypes (Solberg et al.2006), summarized in Table 2 (the names of all pheno-types are given in Table 3).
METHODS
Animals: Original Northport HS mice were obtainedfrom Robert Hitzemann at the Oregon Health SciencesUnit, Portland, Oregon. At the time the animals arrivedthey had passed 50 generations of pseudorandombreeding (Demarest et al. 2001). A breeding colony inopen cages was established at Oxford University togenerate animals for phenotyping. The animals’ pedi-gree comprising the parents and grandparents of thephenotyped animals was recorded.
Phenotypes and covariates: The phenotypes used inthis study and the protocol used to collect them are fullydescribed in Solberg et al. (2006) and summarized inTable 2. We collected 15 covariates (Table 4). Seven aremouse-specific covariates (short names quoted in brack-ets where needed): sex, age, cage identifier (i.e., a unitof shared environment), weight at 9 weeks (‘‘weight’’),number of animals in a cage (‘‘cage density’’), sibship
1Corresponding author: Wellcome Trust Centre for Human Genetics,Roosevelt Dr., Headington, Oxford OX3 7BN, United Kingdom.E-mail valdar@well.ox.ac.uk
Genetics 174: 959–984 (October 2006)
(‘‘family’’), and which litter the mouse came from(‘‘litter’’; e.g., ‘‘3’’ means the animal came from hisparents’ third litter); three are test-specific covariates:experimenter, test order, and apparatus (if more thanone was used); and five covariates are for the time of theexperiment: year, season (the group of three months),month, hour (time rounded to the nearest hour), and‘‘study day,’’ defined as the number of days from start ofthe study on January 20, 2003.
In the analysis, we fitted statistical models for eachphenotype, first testing the significance of each covari-ate as a main effect and then its interaction with geneticbackground. Covariates were either treated as con-tinuous variables [age, cage density, litter, study day(continuous), weight] or encoded as categorical factorstaking discrete levels (apparatus, cage, experimenter,sex, hour, month, season, year, and family). Note thatalthough hour could have been treated as continuous,that would have allowed detection of only linear trends
between time and phenotype, whereas as a factor it canbe used to detect nonlinear relationships.
Statistical analysis: All analysis was carried out usingthe R statistical package (R Development Core Team
2004), along with the add-on packages lme4 (Pinheiro
and Bates 2000), MASS (Venables and Ripley 2002),and regress (Clifford and McCullagh 2005).
We applied normalizing transformations to each phe-notype, guided by the Box–Cox procedure (Venables
and Ripley 2002), and in most cases this comprised asimple exponentiation or log transform to correct skew-ness (see Table 5). Phenotypes with symmetrical buthighly long-tailed distributions were corrected with asimplified Blom transformation (Blom 1958), in whichthe value is replaced by the probit of its empirical dis-tribution function probability. Asymmetric highly skewedlong-tailed distributions best modeled as exponential orgamma distributions were excluded from the analysis, aswere categorical phenotypes and latency phenotypes
TABLE 1
Recent reports of gene-by-environment interactions in mouse
Covariate Phenotype
QTL (i.e., singlelocus) or
polygenic (e.g.,strain) effect
Main-effectvariancea (%)
Interaction-effectvariancea (%) Reference
Laboratory Elevated plus maze Polygenic 32.7b 21b Crabbe et al. (1999)Body weight Polygenic 20.4b 7.1b
Cocaine-induced activity Polygenic 5.3b 8.6b
Sex Body weight Polygenic 63.7b 7b
Open field test Polygenic — 4.5b
Diet Obesity QTL — — York et al. (1999)
Diet (food shortage) Amphetamine-inducedactivity
— — Cabib et al. (2000)
Maternal lactationalenvironment
Plasma glucose Polygenic — — Reifsnyder et al.(2000)
Experimenter Tail-withdrawal latency Polygenic 42 18 Chesler et al. (2002)SexTesting orderTime of day
Laboratory Locomotion Polygenic 11.9–28.4b 10.9–16.5b Wahlsten et al. (2003)Elevated plus maze Polygenic 25.2–30b 13–14.3b
Diet Agressiveness Polygenic — — Nyberg et al. (2004)
Diet Liver weight QTL — — Ehrich et al. (2005)Serum insulin QTL — —Fat pad QTL — —
Diet Liver weight Polygenic — — Biddinger et al. (2005)Leptin Polygenic — —Glucose tolerance test Polygenic — —
Laboratory Open field test Polygenic 0–20.3 0.1–8.7 Kafkafi et al. (2005)
Sex Gonadal fat mass QTL — — Wang et al. (2006)
a The proportion of variance attributable to the main or interaction effect of the covariate, with ‘‘—’’ representing cases wherethis figure was not reported.
b The proportion of variance is given as the partial v2-statistic.
960 W. Valdar et al.
that require survival analysis. After transformation, eachphenotype was trimmed by removing values more than3 standard deviations from the mean to moderate theeffects of outliers.
Modeling the heritability and the effect of common en-vironment: We used a variance-components approachto model the effect of genetic background. Here thegenetic effect on an animal’s phenotype is a value drawnfrom a normal distribution constrained such that thegenetic effects of different animals correlate with theirrelatedness. First we fitted a standard additive genetic,common environmental error, unique environmentalerror (ACE) model to obtain estimates of the propor-tion of phenotypic variance attributable to additivegenetic effects (i.e., the heritability) and to shared en-vironmental effects. Second, we used an approximationto the ACE model that could be extended to test for theeffect of individual environmental covariates.
We formulated the ACE model as follows. Let n be thetotal number of animals, ncage be the number of cages,m be the grand mean, yij be the phenotype of the ithanimal in the jth cage, aij be that animal’s additivegenetic random effect, xijðcÞ be its value for covariate c,bc be the fixed effect associated with covariate c, C be theset of fixed-effect covariates, dj be the random effect of
cage j, and eij be the random effect of uncorrelatedenvironmental noise. Then
yij ¼ m 1X
c2C
bcxijðcÞ1 aij 1 dj 1 eij ; ð1Þ
where, the n-vector e � N ð0;s2EIÞ, the ncage-vector d �
N ð0;s2cageIÞ, and the n-vector g � N ð0;s2
AAÞ, where A isthe n 3 n additive genetic relationship matrix (e.g., seeLynch and Walsh 1998) computed from the pedigree.We estimated the heritability of each phenotype, i.e., theproportion of variance attributable to additive geneticvariation, as h2 ¼ s2
A=s2y and the size of the common
environmental effect as s2cage=s2
y , where s2y is the phe-
notypic variance. The set of covariates chosen for C wassex, litter, and, for phenotypes not directly related tobody mass, weight. Fitting was done by restricted esti-mate maximum likelihood (REML), using the R pack-age regress.
Testing main effects of covariates: For each pheno-type we tested the significance of individual covariatesusing an approximation to the ACE model above. Weemployed a random family effect as a surrogate for thegenetic effect, replacing the random effect ai , specificto individual i, with a random effect fq , specific to familyq. As explained below, this substitution amounts to a
TABLE 2
Summary of phenotypes analyzed, number of animals, and mean age (in days) at which the animals were analyzed
Phenotype Description No. of animals Mean age (days)
Weight, 6 wk Body weight at the beginning of testing. 2516 42Immunology CD4, CD3, CD8, and B220 antibody staining. 1872 42OFT Open field arena: distance in the perimeter, the center, and total
distance in 5 min.2504 45
EPM Elevated plus maze: distance traveled, time spent, and entries intoclosed and open arms.
2452 46
FN Food hyponeophagia: time taken to sample a novel foodstuff(overnight food deprivation).
2474 47
Burrowing No. of pellets removed from burrow in 1.5 hr. 2455 48Activity Activity measured in a home cage in 30 min. 2445 48Startle Startle to a loud noise. 1948 52Context freezing Freezing to the context in which a tone is associated with a foot shock. 2070 55Cue freezing Freezing to a tone after association with a foot shock. 2110 56Plethysmography Animals sensitized by injection with ovalbumin inhale metacholine and
changes in lung function are measured by plethysmography(a model of asthma). Respiratory rate, tidal volume, minute volume,expiratory time, inspiratory time, and enhanced pause are recordedwith and without exposure to metacholine.
2304 63
IPGTT Glucose and insulin values taken at 0, 15, 30, and 75 min after i.p.glucose injection (a model of type 2 diabetes mellitus).
2334 68
Weight, 10 wk Body weight at the end of testing. 2319 70FBC Full blood count (hematocrit, Hb concentration, mean cellular volume,
mean cellular Hb concentration, white cell count, platelet count).1892 71
Tissue harvest Adrenal weight. 2309 71Wound healing Reduction in size of a 2-mm ear punch hole. 2273 71Biochemistry Albumin, alkaline phosphatase, alanine transaminase, aspartate
transaminase, calcium, chloride, creatinine, high-densitylipoprotein, low-density lipoprotein, phosphorous, sodium, totalcholesterol, total protein, triglycerides.
1890 71
Gene–Environment Effects in Mice 961
reparameterization that affects in a predictable fashiononly the estimated variance of random terms. Also,because we wish to examine the effects of individual en-vironmental covariates, we excluded a catch-all randomeffect for cage, which would otherwise be heavily con-founded with any individual environmental covariate.Using notation similar to that above, the model fortesting the significance of covariate c1 was
yiq ¼ m 1X
c2C
bTc xiqðcÞ1 bT
c1xikðc1Þ1 fq 1 eiq ; ð2Þ
where bc are the fixed effects associated with covariate c,xiqðcÞ is the component of the design matrix represent-ing the ith animal’s value for covariate c, bc1
and xiqðc1Þare defined similarly for c1, and fq is such that if thereare nF nuclear families then the nF-vector f � N ð0;s2
FIÞ.We measured the significance of the covariate c1 asthe improvement in fit conferred by covariate c1 aftercertain basic covariates (C) had already been included.The set C usually comprised sex and, for phenotypesnot directly related to body mass, weight. When c1 wasweight, C comprised only sex; when c1 was sex, C wasempty. The significance of the fixed effect c1 was as-sessed using an approximation to the sequential F-test
TABLE 3
Phenotypes assessed in the project
Test Measure
Open field arena Total activityFecal boli
Elevated plus maze Closed-arm distanceOpen-arm distanceClosed-arm timeOpen-arm timeClosed-arm entriesOpen-arm entries
New home-cageactivity
Total beam breaks (30 min)Total beam breaks (first 5 min)Total beam breaks (last 5 min)Fine movement
Context freezing Time freezing to context (sec)Cue conditioning Time freezing during cue (sec)
Time freezing after cue (sec)Fecal boli
Fear-potentiatedstartle
Startle responseChange in startle after training
Plethysmography Enhanced pause (baseline)Enhanced pause (metacholine)Expiratory time (baseline)Expiratory time (metacholine)Inspiratory time (baseline)Inspiratory time (metacholine)PenH differenceRespiratory rate (baseline)Respiratory rate (metacholine)Tidal minute volume (baseline)Tidal minute volume (metacholine)Tidal volume (baseline)Tidal volume (metacholine)
IPGTT AUC-G (mg/dl)AUC-IRI (ng/ml)AUC-IRI/AUC-GDG (mg/dl)DIRI (ng/ml)DIRI/DGGlucose 0 (mg/dl)Glucose 15 (mg/dl)Glucose 30 (mg/dl)Glucose 75 (mg/dl)Insulin 0 (ng/ml)Insulin 15 (ng/ml)Insulin 30 (ng/ml)Insulin 75 (ng/ml)Insulin slopeK (glucose slope)
Immunology %B2201
%CD31
%CD41
%CD41/CD31
%CD81
%CD81/CD31
%NK cellsHematology Hematocrit (%)
Hemoglobin (g/dl)Mean cellular volume (fl)Platelets (n/ml)
(continued)
TABLE 3
(Continued)
Test Measure
Red blood cell count (n/ml)White blood cell count (n/ml)Mean cellular Hb concentration (%)Red cell distribution widthMean corpuscular hemoglobin (pg)LymphocytesPlateletcrit (%)
Biochemistry Alkaline phosphatase (units/liter)Alanine transaminase (units/liter)Aspartate transaminase (units/liter)Albumin (g/liter)Calcium (mmol)Chloride (mmol)High-density lipoproteins (mmol)Low-density lipoproteins (mmol)Phosphorous (mmol)Sodium (mmol)Total cholesterol (mmol)Total protein (g/liter)Triglycerides (mmol)Urea (mmol)
Weight, length,and growth
Body lengthBody mass indexGrowth slopeWeight, 10 wkWeight, 6 wkWeight, 7 wkWeight, 8 wk
Adrenal weight Adrenal weight (g)Wound healing Ear hole area (from ear punch) (mm2)
962 W. Valdar et al.
based on the Wald test (Pinheiro and Bates 2000). Wefit all models by REML using the lmer function from theR package lme4 (Pinheiro and Bates 2000).
Testing interaction effects between covariates andfamily: We define the ‘‘interaction model’’ for thecovariate c1 and family by adding a term to the main-effects model in Equation 3 to allow each family to haveits own effect for that covariate. For factor covariates, theinteraction model included a random intercept nestedwithin family, i.e.,
yiqk ¼ m 1X
c2C
bTc xiqðcÞ1 bT
c1xiqkðc1Þ1 fq 1 uqk 1 eiqk
¼ m 1X
c2C
bTc xiqðcÞ1 bc1k 1 fq 1 uqk 1 eiqk ; ð3Þ
where bc1k is the fixed effect associated with category kof covariate c1, and uqk is the random effect for cate-gory k in family q, such that if there are nU uniquecombinations of category and family then the nU-vectoru � N ð0;s2
UIÞ. For continuous covariates, the interac-tion model included a random slope for c1 conditionedon family, i.e.,
yiq ¼ m 1X
c2C
bTc xiqðcÞ1 ðuq1 1 bc1
ÞTxiqðc1Þ1 fq 1 eiq
¼ m 1X
c2C
bTc xiqðcÞ1 ðuq 1 bc1
Þxiqðc1Þ1 fq 1 eiq ; ð4Þ
where bc1is the fixed coefficient of covariate c1, uq is the
random deviation from that coefficient in family q, andthe correlation between the random intercept f andslope u is unrestricted. We assessed the significance of
the interaction model (Equation 3 or Equation 4) by alikelihood-ratio test (LRT) with the correspondingmain-effects model. Note that by using the change inthe number of degrees of freedom to parameterize thechi-square distribution used for the LRT, our P-valuesfor interaction effects are slightly conservative (Self andLiang 1987). We used the Dunn–Sidak correction, anexact form of the Bonferroni correction (Sahai andAgeel 2000), to take account of the number of testsperformed. For N tests, the corrected 5% threshold islog P ¼ �log10ð1� ð1� 0:05Þ1=N Þ.
The magnitude of a covariate’s effect is defined as thepercentage of phenotypic variance it explains, esti-mated in the model used to test its significance. Forfixed effects, this is the percentage of the total sum ofsquares attributable to the effect in a sequential ANOVAtable after fitting the other covariates (known in someliterature as h2; Olejnik and Algina 2003). For randomeffects, it is the estimated variance of the effect ex-pressed as a percentage of the total phenotypic variance.Where the random effect is based on an interaction withfamily, we report the percentage variance as twice thatof the estimated amount, in accordance with the repa-rameterization formulas described below.
Our use of family as a surrogate for the genetic effectmeans we underestimate the effect size of interactionsby a factor of two. However, this difference is entirelysuperficial. Suppose the n animals are sorted in order oftheir nF nuclear families. When fitting the family ef-fect, the n-vector of random effects is distributed asf � N 0;s2
FF� �
, where the matrix F is block diagonalsuch that Fij is 1 if i and j are in the same sibship and 0
TABLE 4
Covariates used in the study
Covariate Encoding Description Summary
Age Integer Age in days Mean ¼ 61, SD ¼ 4, 31–85Apparatus Categorical Experimental unit used Groups ¼ 4, size ¼ 348–526Cage Categorical Cage in which animal was housed Groups ¼ 435–549, size ¼ 1–7Cage density Integer No. of animals in a cage Mean ¼ 4.7, SD ¼ 1.1, 2–7Experimenter Categorical Who performed the test Groups ¼ 2–12, size ¼ 7–457Family Categorical Sibship of animal Groups ¼ 160–180, size ¼ 1–52Hour Categorical Hour of the day test was performed Groups ¼ 1–11, size ¼ 1–2307Litter Integer No. litter the animal came from Mean ¼ 2.2, SD ¼ 1.3, 1–8Month Categorical Month test was performed Groups ¼ 12, size ¼ 32–314Season Categorical Season test was performed Groups ¼ 4, size ¼ 284–788Sex Categorical Sex of the animal Groups ¼ 2, size ¼ 806–1293Study day Integer Day into study that test was performed
(day 1 is Jan. 20, 2003)Mean ¼ 306, SD ¼ 160, 1–621
Test order Integer Order in which animal was tested that day Mean ¼ 2.8, SD ¼ 1.4, 1–7Weight Real no. Body weight (g) at 9 wk Mean ¼ 23.9, SD ¼ 4.2, 12–39.1Year Categorical Year of test Groups ¼ 2, size ¼ 711–1517
‘‘Encoding’’ refers to how a covariate was modeled statistically. For numerical covariates, the column headed ‘‘Summary’’ givesthe grand mean and standard deviation over all phenotypes, followed by the minimum and maximum values observed for anygiven phenotype. For categorical covariates Summary gives the number and size of categories seen for a typical phenotype. Forexample, for phenotypes in which the experimenter covariate was present, there were between 2 and 12 experimenters who eachrecorded data for between 7 and 457 mice.
Gene–Environment Effects in Mice 963
TABLE 5
Transformations, heritabilities, and common environment effects for 88 phenotypes listed in order of heritability
Phenotype Transformation Category% variance due to additive genetic
variation (i.e., heritability)% variance due to
common environment
%CD81 x Physiological 88.91 11.09CD41/CD81 x�(1/3) Physiological 80.48 14.59Weight, 7 wk (g) x1/3 Physiological 79.36 20.64Weight, 6 wk (g) x1/3 Physiological 74.48 25.52%CD41/CD31 x2 Physiological 72.73 18.48Weight, 8 wk (g) x1/3 Physiological 71.99 18.29High density lipoproteins (mmol) x Physiological 69.11 17.01Alkaline phosphatase (units/liter)
ffiffiffixp
Physiological 62.83 20.47Weight, 10 wk (g) x1/3 Physiological 62.35 18.02%B2201
ffiffiffixp
Physiological 59.86 24.66Glucose 0 (mg/dl)
ffiffiffixp
Physiological 55.33 32.08Red cell distribution width x�2 Physiological 55.29 12.98Mean cellular Hb conc. (%) x Physiological 52.16 39.97%CD31 x2 Physiological 51.30 22.51Ear hole area (mm2)
ffiffiffixp
Physiological 51.02 14.46Mean cellular volume (fl) x Physiological 50.89 20.60Calcium (mmol) x Physiological 48.89 31.39Lymphocytes
ffiffiffixp
Physiological 48.29 17.85Mean corpuscular hemoglobin (pg) x Physiological 47.94 20.24Inspiratory time (metacholine) x�1 Physiological 44.96 10.81Chloride (mmol) x Physiological 44.78 38.43Open-arm distance x1/3 Behavioral 42.06 6.19%CD41 x Physiological 40.70 26.46Startle response x1/3 Behavioral 40.67 4.20White blood cell count (n/ml) log10(x 1 1) Physiological 40.65 23.15Sodium (mmol) x Physiological 39.34 37.83Closed-arm distance x Behavioral 38.81 7.95Open-arm entries
ffiffiffixp
Behavioral 38.57 5.46Open-arm time
ffiffiffixp
Behavioral 37.92 6.08Enhanced pause (baseline) log10(x) Physiological 37.81 26.70Total cholesterol (mmol) x Physiological 37.50 17.62Total beam breaks (30 min)
ffiffiffixp
Behavioral 37.17 11.14Respiratory rate (metacholine) log10(x) Physiological 36.13 12.81Expiratory time (metacholine) log10(x) Physiological 35.00 13.94Glucose 15 (mg/dl)
ffiffiffixp
Physiological 34.83 29.86Total activity x Behavioral 33.86 5.81Inspiratory time (baseline) x�2 Physiological 32.76 16.55Alanine transaminase (units/liter) log10(x 1 3) Physiological 32.20 29.18Respiratory rate (baseline) x Physiological 31.57 18.95Tidal volume (metacholine) x1/3 Physiological 30.95 21.69Low density lipoproteins (mmol) log10(x) Physiological 30.70 18.25Urea (mmol) log10(x 1 1) Physiological 30.59 21.54Growth slope x Physiological 30.52 37.39Time freezing during cue (sec) x Behavioral 30.51 0.00Expiratory time (baseline) log10(x) Physiological 29.52 21.37Fine movement x2 Behavioral 29.45 10.04Total beam breaks (first 5 min)
ffiffiffixp
Behavioral 29.27 12.26Enhanced pause (metacholine) log10(x) Physiological 27.30 28.26Adrenal weight log10(x) Physiological 27.00 36.09Closed-arm time
ffiffiffixp
Behavioral 26.65 7.47Tidal minute volume (metacholine) x1/3 Physiological 26.59 20.01Albumin (g/liter) x Physiological 26.42 22.42Insulin 30 (ng/ml) x1/4 Physiological 26.34 21.62Glucose 75 (mg/dl)
ffiffiffixp
Physiological 26.28 22.94Insulin 15 (ng/ml) log10(x) Physiological 25.85 22.24Time freezing to context (sec)
ffiffiffixp
Behavioral 25.23 12.09PenH difference x1/3 Physiological 25.20 28.85
(continued)
964 W. Valdar et al.
otherwise (note that parents are not included in theanalysis because phenotypes were collected only on theoffspring). The covariance matrix for all random effectsis therefore
V ¼ s2FF 1 s2
EFI; ð5Þ
where s2EF
is the environmental variance when usingfamily for the genetic effect. This models all animalswithin a sibship as if they were genetically identical andall sibships as nuclear. Treating sibships as nuclear isreasonable in our case since the sparsity of our additivegenetic relationship matrix means that A � S, whereSij ¼ 1 when i ¼ j, 0.5 when i and j are sibs, and 0otherwise, and we found empirically that in this data setthe likelihood ratios using the full pedigree A matrixwere very close to those obtained using the nuclearapproximation S. Using the approximation S for A, ourheritability models a covariance matrix
V ¼ s2AS 1 s2
EAI: ð6Þ
Substituting the equality S ¼ 0:5ðF 1 IÞ and equat-ing the coefficients of F and I, it follows that V ¼s2
A0:5� �
F 1 s2A0:5 1 s2
EA
� �I such that when estimated,
s2A ¼ 2s2
F, which agrees with our observed discrepancybetween family-effect size and heritability. Similarlys2
A0:5 1 s2EA¼ s2
EF. Thus the two models are reparame-
terizations of each other. When fitted, they have iden-tical likelihood ratios, and hence 2s2
F is an estimate ofthe true additive genetic variance.
Our estimates of the variance attributable to gene-by-environment effects also rely on the use of the familysurrogate. Applying a similar argument to that above wecan show that those variance estimates are also half whatthey would be if we used the S matrix. The variance ofthe interaction model for categorical covariates (Equa-tion 4) is
V ¼ s2FF 1 s2
MFMF 1 s2
EAI; ð7Þ
where s2MF
is the variance of the interaction and MF is itscorrelation matrix, which is simply F but with Fij ¼ 0
TABLE 5
(Continued)
Phenotype Transformation Category% variance due to additive genetic
variation (i.e., heritability)% variance due to
common environment
Platelets (n/ml) x Physiological 25.07 19.94DIRI/DG x1/4 Physiological 24.61 23.89Triglycerides (mmol) log10(x) Physiological 22.55 21.94AUC-IRI/AUC-G x1/4 Physiological 22.48 22.86Total beam breaks (last 5 min)
ffiffiffixp
Behavioral 22.39 7.58Glucose 30 (mg/dl)
ffiffiffixp
Physiological 22.18 27.00% NK cells x�(1/2) Physiological 21.88 30.24DG (mg/dl) x Physiological 21.82 24.96Body length (cm) x Physiological 21.34 19.92AUC-G (mg/dl) x Physiological 21.24 24.88DIRI (ng/ml) x1/3 Physiological 21.02 19.04Aspartate transaminase (units/liter) x�(1/2) Physiological 20.96 18.47AUC-IRI (ng/ml) x1/2 Physiological 19.24 18.87Closed-arm entries x Behavioral 19.20 7.00Tidal volume (baseline) x1/3 Physiological 18.56 25.07Insulin 0 (ng/ml) log10(x) Physiological 17.83 26.01Tidal minute volume (baseline) x1/3 Physiological 16.51 22.21Phosphorous (mmol) log10(x 1 1) Physiological 16.10 28.41Insulin slope x1/3 Physiological 15.21 6.49Red blood cell count (n/ml) x3 Physiological 15.14 18.00Hemoglobin (g/dl) x3 Physiological 15.12 17.83Time freezing after cue (sec) x Behavioral 13.81 0.00Change in startle after training Blom(x) Behavioral 13.61 4.48Fecal boli
ffiffiffiffiffiffiffiffiffiffiffix 1 1p
Behavioral 13.38 13.02Body mass index x Physiological 13.21 14.75Insulin 75 (ng/ml) x1/3 Physiological 13.11 26.72Plateletcrit (%)
ffiffiffixp
Physiological 12.91 20.24Hematocrit (%) x3 Physiological 10.86 18.98Fecal boli after cue
ffiffiffixp
Behavioral 9.91 6.97Total protein (g/liter) x2 Physiological 8.51 28.59K (glucose slope) x1/2 Physiological 7.60 10.28
Transformations use the following conventions: x¼ phenotype; log10, log to base 10; Blom, replace each point with the probit ofits relative cumulative frequency.
Gene–Environment Effects in Mice 965
when animals i and j are in different categories. If wewere to use S (an approximation for A) in place of F wewould have
V ¼ s2AS 1 s2
MAMS 1 s2
EAI; ð8Þ
with s2MA
being the interaction between the categoricalcovariate and the additive genetic effect. However, sinceS ¼ 0:5ðF 1 IÞ and MS ¼ 0:5ðMF 1 IÞ, it follows thatV ¼ s2
A0:5� �
F 1 s2MA
0:5� �
MF 1 s2A0:5 1 s2
MA0:5 1 s2
EA
� �I
and therefore s2MA¼ 2s2
MF. For interactions between a
continuous covariate x and family (Equation 5) thevariance is
V ¼ s2FF 1 s2
MFZFZT 1 s2
EAI; ð9Þ
where Z ¼ diagðxÞ when x is the n-vector of x for the nanimals. If we were to use S-approximation for A thevariance would be
V ¼ s2AS 1 s2
MAZSZT 1 s2
EAI: ð10Þ
Substituting S ¼ 0:5ðF 1 IÞ as before, V ¼ s2A0:5
� �F 1
s2MA
0:5� �
ZFZT 1 s2MA
0:5ZZT 1 s2A0:5 1 s2
EA
� �� �I, which
implies s2MA¼ 2s2
MF. Hence, in all cases the estimated var-
iance of an additive genetic component is simply twicethat of the corresponding family component.
RESULTS
Of the 102 phenotypes available for analysis (Solberg
et al. 2006), 88 could be accommodated in our linearmixed modeling framework (see methods). We ob-tained data for 15 covariates (Table 4): age, apparatus(for those tests where multiple units were used), cage(a variable indicating animals that were housed in thesame cage), cage density (the number of animals in acage), experimenter, family (defined as the offspring oftwo parents), sex, hour, litter (a number represent-ing the birth order of each litter for a given sire anddam), month, season, study day, test order, weight, andyear. An average of 10.3 covariates were recorded perphenotype (since not all phenotype–covariate combi-nations were available), leading to an average of 69.4phenotypes measured per covariate. In total, we per-formed 1804 statistical tests. The significance of resultsis reported as the negative base 10 logarithm of theP-value (log P) of the relevant test. We took account ofmultiple testing by using the Dunn–Sidak correction,which for a ¼ 5% comparisonwise error rate yielded asignificance threshold of log P ¼ 4.55.
We assessed initially the importance of three physio-logical covariates (sex, weight, and age). We fitted thecovariates sequentially in the order sex, then weight,then age, so that, for instance, our reported significancefor weight refers to how much it improved the fit of amodel that already included sex. We included family inall models to ensure tested covariates were significantover and above genetic effects. Family, modeled as a
random effect, is highly correlated with heritability(correlation of 0.89) and so acts a surrogate for theeffect of additive genetic variation (see methods). Wereport estimates of heritability for all phenotypes inTable 5.
The effects of sex, weight, and age were relativelysmall (Figure 1b, ‘‘main effect’’ rows): sex effects ex-plained .10% of the variance for 14 phenotypes; inmore than half of the cases the effect was ,5%; weightaccounted for .10% of the variance for three pheno-types; all age effects were ,2% (see appendix).
We estimated the significances and effects of theremaining covariates by adding each to a model thatalready included family, sex, and weight. Significantmain effects of covariates were more common in phys-iological than behavioral phenotypes (33% of the timevs. 13%; see Table 6). Overall, 21 of the 258 significanteffects explained .10% of the variance; the five cases ofwhen a covariate explained .25% of the variance in-volved sex. Table 6 provides a summary for each covar-iate, splitting results by category of phenotype. Figure 1plots log P-values and the percentage of phenotypicvariance explained by significant covariates. Figure 2summarizes the variance explained by significant covar-iates for the 16 subcategories of phenotype.
We then extended our model to test for gene-by-covariate interactions, taking the main-effects modelsreported above and then assessing how much addinginteraction terms improved the fit. We found 389significant interaction effects. Figure 3 illustrates theinteraction between sex and family on the percentage ofB-cells (%B2201) among white blood cells. It shows thatthe effect of sex is often marked within families but itsdirection can vary between families. Similarly, Figure 4illustrates the interaction between family and season onmean adrenal weight measured at 10 weeks. It shows sea-sonal means (spring in green, summer in red, autumnin brown, and winter in blue) for 28 families. In 11families, adrenal glands are heaviest when harvested inwinter, whereas in 9 families they are heaviest in sum-mer. The seasonal effects are strong within but incon-sistent across families, reflecting the greater importanceof interaction over main effects.
The distribution of the 389 significant interactioneffects differed from that of the main effects (Figure 1and appendix). Remarkably, half of the effects couldexplain .20% of the variance. In nine cases the in-teraction could explain .50% of the variance. Thelargest numbers of interactions were with month (65significant effects), season (55), sex (53), litter (51), andcage density (40). There were only 13 significant in-teractions with experimenter.
Physiological phenotypes showed the largest num-ber of interactions with covariates (56% of interac-tions tested were significant; Table 7). Largest effectswere found on mean cellular hemoglobin concentra-tion, serum sodium and serum chloride concentrations,
966 W. Valdar et al.
and plethysmography measures. There were fewer in-teractions with behavioral phenotypes (5% of interac-tions tested were significant, amounting to 11 in total),although the effect sizes were much the same on average(mean of 18.1% for behavior compared with a mean of18.6% for physiology; see Figure 2).
DISCUSSION
We have carried out the first systematic analysis ofa range of covariates across multiple phenotypes(see appendix). We have estimated the heritability of88 phenotypes, assessed the impact of a number of
Figure 1.—Main effects and interactions. (a)The log P (i.e., the�log10 of the P-value) for mainand interaction effects of 12 covariates. Each boxshows significance scores for one covariate on allapplicable phenotypes. The shaded bar marksthe corrected 5% threshold for significance(log P¼ 4.55). For example, Apparatus has signif-icant main effects for a few phenotypes but signif-icant interactions for none, whereas Hour has fewsignificant main effects but has significant inter-action effect for a number of phenotypes. (b)The estimated percentage of variance significanteffects contributed to the phenotype. Note thatlog P ’s are capped at 20 for display purposes andthat results for test order, which had no significanteffects, are not shown.
TABLE 6
Summary of main effects
Physiological phenotypes Behavioral phenotypes
Covariate Median log PMean %variance SD
No. observed(significant/all)
Medianlog P
Mean %variance SD
No. observed(significant/all)
Age 0.82 0.98 0.40 6/65 0.73 0.86 0.17 3/18Apparatus — — — — 31.59 7.80 3.47 4/5Cage density 1.01 0.68 0.34 9/70 0.84 — — 0/18Experimenter 2.04 3.30 2.44 7/25 2.50 1.80 0.56 6/20Hour 1.55 1.16 — 1/29 1.51 1.41 — 1/20Litter 0.97 0.90 0.31 9/70 0.88 — — 0/18Month 8.96 3.56 2.24 51/65 2.14 1.75 — 1/18Season 5.47 1.90 1.25 38/65 1.57 — — 0/18Sex 12.41 9.47 11.62 48/70 2.06 2.19 1.79 5/18Study day 1.00 2.03 1.60 15/65 1.27 0.73 — 1/18Test order 0.37 — — 0/25 0.72 — — 0/16Weight 2.92 3.06 3.89 27/65 2.06 0.90 0.23 6/18Year 1.87 1.30 0.71 19/65 1.61 0.85 — 1/18
Variances (means and standard deviations) refer only to effects that were significant at log P . 4.55.
Gene–Environment Effects in Mice 967
environmental factors, and measured the size of gene-by-environment interactions. Our large data set pro-vides the most robust assessments to date of thesemeasures in both behavioral and physiological domains.
We found large interactions between gene and envi-ronment and report that the effects are not restricted tobehavioral phenotypes (see appendix). We do notbelieve this is an artifact of our analysis. Our calculationsof percentage variance for random interaction effectsand for fixed main effects are only roughly comparablewith each other (see methods) and the interaction ef-fects are subject to a slight upward bias. However, that isnot sufficient to account for the substantially highereffect of significant interactions (18.6%) compared withsignificant main effects (3.7%). Second, inhomogeneityof phenotype variance across families is also unlikelyto account for our findings since in many cases therank order of covariate effects differs between families(Ungerer et al. 2003) as illustrated in Figures 3 and 4.
We report the effects of covariates as the percentageof phenotypic variance they explain and in doing soprovide one assessment of how environmental covari-ates influence a phenotype. But the true nature of this
interaction is more complex. For example, the concen-tration of alanine transaminase is subject to gene-by-environment interactions of month, accounting for48.49% of the phenotypic variance, of season, account-ing for 45.51%, and of litter, accounting for 18.17%. Yetthese effects combine, with further covariates, to pro-duce 100%. How is this possible?
The correlational structure of our data complicatesan assessment of the relative importance of differentcovariates and interactions. The observed phenotypicvariance is the sum of the variances of the covariatesminus twice the covariances between the covariates.This means that two covariates could have individualeffects of 50% but a summed effect of 60% if they arepositively correlated (or one of ,50% if they are nega-tively correlated). An observed covariate effect, just likean observed QTL effect, therefore includes a portion ofthe effect of any element that correlates with it; an actualmonth effect will partly manifest as observed litter andseason effects and vice versa. A more comprehensiveanalysis would build a complete picture of each pheno-type in the context of a path diagram or structuralequation model that enumerated all relationships, both
Figure 2.—Main and interaction effects of co-variates on 88 phenotypes from 16 experimentaltests. The y-axis gives the percentage variance ex-plained by significant covariates; the x-axis liststhe test performed with the number of pheno-types measured from that test in parentheses.Physiological tests are listed first and behavioraltests second. Boxes show the median (centralline) and interquartile range (IQR; box perime-ter), whiskers indicate the furthest data point,1.58 IQRs from the median, and circles showoutliers.
Figure 3.—Interaction between sex and familyfor the immunological phenotype percentage ofB-cells among lymphocytes in 2056 mice. Foreach of 69 families (x-axis) we plot means (solidcircles) and standard errors (bars) of the pheno-type value for males (blue) and females (pink).The y-axis gives the phenotype as the square rootof the percentage of white blood cells presentingB220. The graph shows that sex can have a strongeffect within families but that the direction of theeffect varies between families (interaction log P¼10.7). For example, in families plotted on the left,males are enriched in the B-cell compared with fe-males, whereas for families on the right this sex ef-
fect is reversed. The graph also illustrates the marginal effects on the trait of family (differing overall heights; heritability¼ 59.9%)and sex (females higher overall; main effect log P ¼ 13.0).
968 W. Valdar et al.
raw effects and correlations, between actors (e.g., Lynch
and Walsh 1998).The importance of gene-by-environment interactions
has been emphasized in the analysis of mouse behaviorand largely ignored in studies of mouse physiology. Inthe light of this, we designed our phenotyping protocolto minimize the effects of covariates on behavioralmeasures. All such tests were automated, so that theexperimenter’s intervention was limited to placing ani-mals in the apparatus. This may explain why some co-variates, previously suspected to influence behavioralphenotypes, were found to make a small contribution tothe variance: time of day (hour) was a nonsignificant (orhardly significant with negligible effect) contributor toall measures including those that utilize explorationas a measure of anxiety (elevated plus maze, which hadobservations from 9 different hours of the day, andopen field, which had observations from 10), despitethe fact that exploratory activity has been reported tovary throughout the day (Aschoff 1981). The order in
which animals are tested is also considered to have animportant effect on behavior (Harro 1997), but wefound no evidence for this: its effect was nonsignificanton all phenotypes measured.
Physiological phenotypes were not so controlled.There are no automated ways of administering an intra-peritoneal glucose tolerance test, for example, and weobserved large experimenter effects on these tests. Thisraises the question as to whether some phenotypesare more susceptible to interaction effects than others.Differences in the assessment protocols cannot be theonly factor that accounts for the smaller number ofinteractions in behavioral tests. There are a number ofcovariates common to all phenotypes whose effectswe could not ameliorate: month, season, year, sex, andweight. All of these covariates impinge more on physi-ological than on behavioral phenotypes (Tables 6 and 7).
Importantly, we observed many significant and largegene-by-environment interactions in our analysis ofphysiological phenotypes. Biochemical measures showed
Figure 4.—Interaction between season andfamily for the physiological phenotype mean ad-renal weight in 696 mice. For each of 28 families(x-axis) we plot the seasonal means (solid circles)and standard errors (bars) of the phenotype foranimals phenotyped in winter (blue), spring(green), summer (red), and autumn (brown).The y-axis gives the phenotype as the logarithmto the base 10 of the mean weight in grams of ad-renal glands at 10 weeks old. The graph showsthat the effect of season is consistent within familybut can vary between families. For example, forthe rightmost family adrenal glands are lightestin animals tested in summer and heaviest in au-tumn. Yet the rank order of seasons varies consid-erably through the graph.
TABLE 7
Summary of interaction effects between covariates and family
Physiological phenotypes Behavioral phenotypes
CovariateMedian
log PMean %variance SD
No. observed(significant/all)
Medianlog P
Mean %variance SD
No. observed(significant/all)
Age 2.39 1.22 0.59 26/65 0.25 — — 0/18Apparatus — — — — 0.00 — — 0/5Cage density 5.05 10.80 4.45 40/70 0.37 — — 0/18Experimenter 4.28 26.41 6.89 11/25 2.35 16.65 1.62 2/20Hour 6.17 23.69 7.78 21/29 1.96 — — 0/20Litter 9.17 13.58 7.21 51/70 0.53 — — 0/18Month 11.84 29.94 11.63 60/65 3.87 18.49 3.50 5/18Season 8.04 29.24 11.66 52/65 2.25 18.94 3.92 3/18Sex 6.82 22.33 6.66 52/70 2.21 16.38 — 1/18Study day 2.86 0.03 0.02 22/65 0.39 — — 0/18Test order 0.21 — — 0/25 0.00 — — 0/16Weight 3.88 0.59 0.14 28/65 1.39 — — 0/18Year 2.09 39.77 15.72 15/65 0.69 — — 0/18
Variances (means and standard deviations) refer only to effects that were significant at log P . 4.55.
Gene–Environment Effects in Mice 969
strong (.10% effect) gene-by-environment interactionswith month (in 14 of 16 biochemical phenotypes), sex(12), season (9), and litter (8). We saw a similar patternof strong seasonal and sex effects for hematology, im-munology, plethysmography (which also had a stronghour interaction), and the glucose tolerance test (whichalso had a strong experimenter interaction). This hasprofound implications for QTL studies.
QTL detection experiments suffer when covariatesare not adequately accommodated in the experimentaldesign and subsequent analysis. First, a QTL may owesome, or indeed all, of its significance to an environ-mental effect confounded with the allelic variant. Whena phenotype is strongly affected by who performed theexperiment, any nonfunctional variant that correlateswith the experimenter will manifest as a significant, butspurious, effect. The random nature of recombinationmeans that in any experimental cross a fully balanceddesign is impossible and so confounds of this type areineluctable. While the impact of covariates can be mini-mized by regressing out their effects prior to mapping(e.g., Valdar et al. 2006), this is highly conservative,since in the converse scenario, where experimenter actsas a surrogate variable for an actual QTL effect, the QTLwill be missed.
Second, an interaction between a QTL and an envi-ronmental covariate may conceal the effect of both,even when covariate and QTL are in the model. Forinstance, if mice with allele a fear experimenter Johnmore than experimenter Alice, but mice with allele Afear Alice more than John and all four conditions occurin about equal proportion, then neither experimenternor QTL will have an observed effect. To recover thegenetic effect in this case it is necessary to model theinteraction in the mapping procedure (e.g., Wang et al.2006).
Our analyses are limited by the relatively smallnumber of covariates that we collected. We have noinformation on temperature fluctuation and humiditylevels [shown to be important for behavioral tests ofnociception (Chesler et al. 2002a,b)], which mightexplain month and seasonal effects. We have no in-formation on noise levels that are significantly increasedduring working hours (Milligan et al. 1993). The pre-dominance of significant temporal covariates reflectsthe importance of many other unknown environmentalfactors whose effect is moderated through the animals’genotypes. Thus the dissection of complex phenotypesin the mouse will require far more sophisticated ob-servation and analysis of these interactions than hashitherto been attempted.
W.V. gratefully acknowledges receipt of an Access to ResearchInfrastructures fellowship under Orjan Carlborg, Uppsala University,Sweden, and additionally thanks Mike Neale, Tom Price, and PeterVisscher for helpful discussions. This work was funded by grantsfrom the Wellcome Trust and the European Union Framework 6Programme, contract no. LHSG-CT-2003-503265.
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Communicating editor: G. Gibson
Gene–Environment Effects in Mice 971
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932.
3517
.78
31.7
2B
ioch
emis
try
Alk
alin
ep
ho
sph
atas
e(u
nit
s/li
ter)
Seas
on
1701
——
10.6
426
.09
Bio
chem
istr
yA
lkal
ine
ph
osp
hat
ase
(un
its/
lite
r)Se
x20
2111
.28
1.49
11.7
723
.24
Bio
chem
istr
yA
lkal
ine
ph
osp
hat
ase
(un
its/
lite
r)St
ud
yd
ay17
01—
—6.
200.
02B
ioch
emis
try
Alk
alin
ep
ho
sph
atas
e(u
nit
s/li
ter)
Year
1701
——
4.95
24.4
5B
ioch
emis
try
Asp
arta
tetr
ansa
min
ase
(un
its/
lite
r)L
itte
r19
33—
—9.
8310
.96
Bio
chem
istr
yA
spar
tate
tran
sam
inas
e(u
nit
s/li
ter)
Mo
nth
1629
9.03
3.02
8.89
25.0
9B
ioch
emis
try
Asp
arta
tetr
ansa
min
ase
(un
its/
lite
r)Se
aso
n16
295.
731.
3510
.02
27.8
7B
ioch
emis
try
Asp
arta
tetr
ansa
min
ase
(un
its/
lite
r)Se
x19
4227
.03
4.91
——
Bio
chem
istr
yA
spar
tate
tran
sam
inas
e(u
nit
s/li
ter)
Stu
dy
day
1629
25.5
25.
27—
—B
ioch
emis
try
Asp
arta
tetr
ansa
min
ase
(un
its/
lite
r)W
eigh
t19
4210
.20
1.72
——
Bio
chem
istr
yA
spar
tate
tran
sam
inas
e(u
nit
s/li
ter)
Year
1629
7.03
1.35
5.49
27.4
2
(con
tin
ued
)
972 W. Valdar et al.
AP
PE
ND
IX
(Co
nti
nu
ed)
Mai
nef
fect
sIn
tera
ctio
ns
Tes
tP
hen
oty
pe
Co
vari
ate
No
.o
bse
rved
log
P%
vari
ance
exp
lain
edlo
gP
%va
rian
ceex
pla
ined
Bio
chem
istr
yC
alci
um
(mm
ol)
Age
1688
——
4.70
0.77
Bio
chem
istr
yC
alci
um
(mm
ol)
Cag
ed
ensi
ty20
04—
—4.
728.
84B
ioch
emis
try
Cal
ciu
m(m
mo
l)L
itte
r19
94—
—13
.69
15.8
9B
ioch
emis
try
Cal
ciu
m(m
mo
l)M
on
th16
8812
.22
3.66
14.9
535
.51
Bio
chem
istr
yC
alci
um
(mm
ol)
Seas
on
1688
6.95
1.59
13.6
038
.72
Bio
chem
istr
yC
alci
um
(mm
ol)
Sex
2004
11.4
81.
6515
.18
32.1
8B
ioch
emis
try
Cal
ciu
m(m
mo
l)St
ud
yd
ay16
8813
.11
2.55
10.2
80.
02B
ioch
emis
try
Cal
ciu
m(m
mo
l)W
eigh
t20
0410
.36
1.48
11.4
20.
83B
ioch
emis
try
Cal
ciu
m(m
mo
l)Ye
ar16
8811
.79
2.26
——
Bio
chem
istr
yC
hlo
rid
e(m
mo
l)A
ge17
44—
—13
.36
2.21
Bio
chem
istr
yC
hlo
rid
e(m
mo
l)C
age
den
sity
2068
——
7.82
11.1
0B
ioch
emis
try
Ch
lori
de
(mm
ol)
Lit
ter
2058
——
26.6
038
.71
Bio
chem
istr
yC
hlo
rid
e(m
mo
l)M
on
th17
447.
692.
3943
.88
69.0
6B
ioch
emis
try
Ch
lori
de
(mm
ol)
Seas
on
1744
——
30.2
870
.86
Bio
chem
istr
yC
hlo
rid
e(m
mo
l)Se
x20
6823
.74
3.32
20.7
435
.48
Bio
chem
istr
yC
hlo
rid
e(m
mo
l)St
ud
yd
ay17
448.
331.
4214
.12
0.02
Bio
chem
istr
yC
hlo
rid
e(m
mo
l)W
eigh
t20
6810
.63
1.40
14.0
40.
78B
ioch
emis
try
Hig
h-d
ensi
tyli
po
pro
tein
s(m
mo
l)A
ge16
12—
—5.
360.
45B
ioch
emis
try
Hig
h-d
ensi
tyli
po
pro
tein
s(m
mo
l)M
on
th16
12—
—5.
8612
.67
Bio
chem
istr
yH
igh
-den
sity
lip
op
rote
ins
(mm
ol)
Sex
1912
173.
5522
.74
14.9
621
.61
Bio
chem
istr
yH
igh
-den
sity
lip
op
rote
ins
(mm
ol)
Stu
dy
day
1612
4.58
0.49
——
Bio
chem
istr
yH
igh
-den
sity
lip
op
rote
ins
(mm
ol)
Wei
ght
1912
19.4
62.
0114
.86
0.71
Bio
chem
istr
yH
igh
-den
sity
lip
op
rote
ins
(mm
ol)
Year
1612
5.34
0.58
——
Bio
chem
istr
yL
ow
-den
sity
lip
op
rote
ins
(mm
ol)
Cag
ed
ensi
ty19
47—
—4.
778.
53B
ioch
emis
try
Lo
w-d
ensi
tyli
po
pro
tein
s(m
mo
l)M
on
th16
469.
203.
055.
5418
.53
Bio
chem
istr
yL
ow
-den
sity
lip
op
rote
ins
(mm
ol)
Sex
1947
13.4
42.
327.
7319
.19
Bio
chem
istr
yP
ho
sph
oro
us
(mm
ol)
Age
1495
6.27
1.41
——
Bio
chem
istr
yP
ho
sph
oro
us
(mm
ol)
Mo
nth
1495
——
12.7
740
.25
Bio
chem
istr
yP
ho
sph
oro
us
(mm
ol)
Seas
on
1495
——
5.77
26.5
4B
ioch
emis
try
Ph
osp
ho
rou
s(m
mo
l)Se
x17
83—
—5.
2124
.81
Bio
chem
istr
yP
ho
sph
oro
us
(mm
ol)
Stu
dy
day
1495
4.86
1.05
——
Bio
chem
istr
yP
ho
sph
oro
us
(mm
ol)
Year
1495
8.05
1.84
——
Bio
chem
istr
ySo
diu
m(m
mo
l)A
ge17
34—
—9.
721.
85B
ioch
emis
try
Sod
ium
(mm
ol)
Lit
ter
2048
——
28.5
433
.14
Bio
chem
istr
ySo
diu
m(m
mo
l)M
on
th17
346.
632.
1037
.62
62.0
2B
ioch
emis
try
Sod
ium
(mm
ol)
Seas
on
1734
——
21.6
250
.65
Bio
chem
istr
ySo
diu
m(m
mo
l)Se
x20
5834
.14
5.01
17.4
531
.96
Bio
chem
istr
ySo
diu
m(m
mo
l)St
ud
yd
ay17
347.
041.
1711
.85
0.02
Bio
chem
istr
ySo
diu
m(m
mo
l)W
eigh
t20
5814
.14
1.96
12.6
40.
76 (con
tin
ued
)
Gene–Environment Effects in Mice 973
AP
PE
ND
IX
(Co
nti
nu
ed)
Mai
nef
fect
sIn
tera
ctio
ns
Tes
tP
hen
oty
pe
Co
vari
ate
No
.o
bse
rved
log
P%
vari
ance
exp
lain
edlo
gP
%va
rian
ceex
pla
ined
Bio
chem
istr
ySo
diu
m(m
mo
l)Ye
ar17
347.
081.
17—
—B
ioch
emis
try
To
tal
cho
lest
ero
l(m
mo
l)M
on
th17
0415
.12
3.48
6.68
16.0
2B
ioch
emis
try
To
tal
cho
lest
ero
l(m
mo
l)Se
aso
n17
0411
.76
2.09
——
Bio
chem
istr
yT
ota
lch
ole
ster
ol
(mm
ol)
Sex
2018
97.5
915
.23
5.81
14.0
8B
ioch
emis
try
To
tal
cho
lest
ero
l(m
mo
l)W
eigh
t20
185.
430.
66—
—B
ioch
emis
try
To
tal
pro
tein
(g/
lite
r)C
age
den
sity
1882
——
5.86
10.4
0B
ioch
emis
try
To
tal
pro
tein
(g/
lite
r)M
on
th15
6516
.74
5.29
12.8
640
.36
Bio
chem
istr
yT
ota
lp
rote
in(g
/li
ter)
Seas
on
1565
12.9
13.
238.
3840
.76
Bio
chem
istr
yT
ota
lp
rote
in(g
/li
ter)
Sex
1882
12.4
92.
345.
7120
.71
Bio
chem
istr
yT
ota
lp
rote
in(g
/li
ter)
Stu
dy
day
1565
——
5.86
0.02
Bio
chem
istr
yT
ota
lp
rote
in(g
/li
ter)
Wei
ght
1882
8.64
1.57
——
Bio
chem
istr
yT
rigl
ycer
ides
(mm
ol)
Cag
ed
ensi
ty17
38—
—7.
3010
.48
Bio
chem
istr
yT
rigl
ycer
ides
(mm
ol)
Mo
nth
1448
——
6.31
20.7
9B
ioch
emis
try
Tri
glyc
erid
es(m
mo
l)Se
x17
3885
.67
16.3
4—
—B
ioch
emis
try
Ure
a(m
mo
l)C
age
den
sity
1992
——
8.79
13.8
8B
ioch
emis
try
Ure
a(m
mo
l)L
itte
r19
82—
—10
.54
11.8
6B
ioch
emis
try
Ure
a(m
mo
l)M
on
th16
736.
802.
448.
5824
.17
Bio
chem
istr
yU
rea
(mm
ol)
Seas
on
1673
5.68
1.35
——
Bio
chem
istr
yU
rea
(mm
ol)
Sex
1992
——
10.6
227
.54
Co
nte
xtfr
eezi
ng
Tim
efr
eezi
ng
toco
nte
xt(s
ec)
Ap
par
atu
s16
7118
.88
4.13
——
Co
nte
xtfr
eezi
ng
Tim
efr
eezi
ng
toco
nte
xt(s
ec)
Exp
erim
ente
r16
715.
221.
70—
—C
on
text
free
zin
gT
ime
free
zin
gto
con
text
(sec
)Se
x16
7124
.20
5.14
——
Co
nte
xtfr
eezi
ng
Tim
efr
eezi
ng
toco
nte
xt(s
ec)
Wei
ght
1671
6.04
1.14
——
Cu
eco
nd
itio
nin
gF
ecal
bo
liaf
ter
cue
Sex
1768
4.80
0.98
——
Cu
eco
nd
itio
nin
gT
ime
free
zin
gaf
ter
cue
(sec
)A
ge17
915.
081.
05—
—C
ue
con
dit
ion
ing
Tim
efr
eezi
ng
afte
rcu
e(s
ec)
Ap
par
atu
s16
6543
.68
10.9
8—
—C
ue
con
dit
ion
ing
Tim
efr
eezi
ng
du
rin
gcu
e(s
ec)
Ap
par
atu
s16
6546
.03
10.5
4—
—E
leva
ted
plu
sm
aze
Clo
sed
-arm
entr
ies
Exp
erim
ente
r22
294.
571.
44—
—E
leva
ted
plu
sm
aze
Clo
sed
-arm
entr
ies
Wei
ght
2229
5.68
0.89
——
Ele
vate
dp
lus
maz
eC
lose
d-a
rmti
me
Mo
nth
2221
——
4.98
15.6
1E
leva
ted
plu
sm
aze
Op
en-a
rmd
ista
nce
Exp
erim
ente
r22
617.
141.
71—
—E
leva
ted
plu
sm
aze
Op
en-a
rmd
ista
nce
Mo
nth
2260
——
7.52
17.0
6E
leva
ted
plu
sm
aze
Op
en-a
rmd
ista
nce
Wei
ght
2261
4.82
0.63
——
Ele
vate
dp
lus
maz
eO
pen
-arm
entr
ies
Wei
ght
2261
5.90
0.80
——
Ele
vate
dp
lus
maz
eO
pen
-arm
tim
eE
xper
imen
ter
2261
6.78
1.69
——
Ele
vate
dp
lus
maz
eO
pen
-arm
tim
eM
on
th22
60—
—7.
1817
.03
Ele
vate
dp
lus
maz
eO
pen
-arm
tim
eW
eigh
t22
615.
300.
72—
—F
ear
po
ten
tiat
edst
artl
eSt
artl
ere
spo
nse
Age
2005
5.40
0.82
——
Fea
rp
ote
nti
ated
star
tle
Star
tle
resp
on
seA
pp
arat
us
2005
31.5
95.
54—
— (con
tin
ued
)
974 W. Valdar et al.
AP
PE
ND
IX
(Co
nti
nu
ed)
Mai
nef
fect
sIn
tera
ctio
ns
Tes
tP
hen
oty
pe
Co
vari
ate
No
.o
bse
rved
log
P%
vari
ance
exp
lain
edlo
gP
%va
rian
ceex
pla
ined
Fea
rp
ote
nti
ated
star
tle
Star
tle
resp
on
seSe
x20
0515
.69
2.65
——
Fea
rp
ote
nti
ated
star
tle
Star
tle
resp
on
seSt
ud
yd
ay20
054.
860.
73—
—F
ear
po
ten
tiat
edst
artl
eSt
artl
ere
spo
nse
Wei
ght
2005
7.53
1.19
——
Fea
rp
ote
nti
ated
star
tle
Star
tle
resp
on
seYe
ar20
055.
600.
85—
—G
luco
seto
lera
nce
test
AU
C-G
(mg/
dl)
Age
2130
——
5.36
0.94
Glu
cose
tole
ran
cete
stA
UC
-G(m
g/d
l)C
age
den
sity
2130
——
8.35
12.5
1G
luco
seto
lera
nce
test
AU
C-G
(mg/
dl)
Exp
erim
ente
r21
309.
452.
118.
7726
.37
Glu
cose
tole
ran
cete
stA
UC
-G(m
g/d
l)H
ou
r21
30—
—5.
0416
.56
Glu
cose
tole
ran
cete
stA
UC
-G(m
g/d
l)L
itte
r21
17—
—12
.48
11.9
6G
luco
seto
lera
nce
test
AU
C-G
(mg/
dl)
Mo
nth
2130
4.74
1.59
18.7
136
.65
Glu
cose
tole
ran
cete
stA
UC
-G(m
g/d
l)Se
aso
n21
305.
101.
017.
8025
.18
Glu
cose
tole
ran
cete
stA
UC
-G(m
g/d
l)St
ud
yd
ay21
30—
—5.
600.
01G
luco
seto
lera
nce
test
AU
C-G
(mg/
dl)
Wei
ght
2130
——
6.26
0.53
Glu
cose
tole
ran
cete
stA
UC
-IR
I(n
g/m
l)C
age
den
sity
2105
——
5.10
7.54
Glu
cose
tole
ran
cete
stA
UC
-IR
I(n
g/m
l)M
on
th21
05—
—10
.38
24.6
5G
luco
seto
lera
nce
test
AU
C-I
RI
(ng/
ml)
Seas
on
2105
——
4.63
16.3
5G
luco
seto
lera
nce
test
AU
C-I
RI
(ng/
ml)
Sex
2105
——
7.95
21.3
3G
luco
seto
lera
nce
test
AU
C-I
RI
(ng/
ml)
Wei
ght
2105
6.66
1.07
——
Glu
cose
tole
ran
cete
stA
UC
-IR
I/A
UC
-GC
age
den
sity
1982
——
6.51
10.9
2G
luco
seto
lera
nce
test
AU
C-I
RI/
AU
C-G
Lit
ter
1970
——
5.85
8.22
Glu
cose
tole
ran
cete
stA
UC
-IR
I/A
UC
-GM
on
th19
82—
—10
.08
26.8
5G
luco
seto
lera
nce
test
AU
C-I
RI/
AU
C-G
Seas
on
1982
——
5.08
19.6
5G
luco
seto
lera
nce
test
AU
C-I
RI/
AU
C-G
Sex
1982
——
6.70
19.9
6G
luco
seto
lera
nce
test
DG
(mg/
dl)
Age
2131
——
5.88
1.01
Glu
cose
tole
ran
cete
stD
G(m
g/d
l)C
age
den
sity
2131
——
8.53
12.8
2G
luco
seto
lera
nce
test
DG
(mg/
dl)
Exp
erim
ente
r21
3111
.18
2.43
9.80
28.1
5G
luco
seto
lera
nce
test
DG
(mg/
dl)
Ho
ur
2131
——
5.36
17.2
9G
luco
seto
lera
nce
test
DG
(mg/
dl)
Lit
ter
2118
——
12.7
512
.24
Glu
cose
tole
ran
cete
stD
G(m
g/d
l)M
on
th21
315.
151.
6818
.64
36.7
2G
luco
seto
lera
nce
test
DG
(mg/
dl)
Seas
on
2131
5.79
1.13
7.61
25.0
2G
luco
seto
lera
nce
test
DG
(mg/
dl)
Stu
dy
day
2131
——
5.87
0.01
Glu
cose
tole
ran
cete
stD
G(m
g/d
l)W
eigh
t21
31—
—6.
620.
56G
luco
seto
lera
nce
test
DIR
I(n
g/m
l)C
age
den
sity
2107
——
5.14
7.64
Glu
cose
tole
ran
cete
stD
IRI
(ng/
ml)
Lit
ter
2095
——
5.02
6.49
Glu
cose
tole
ran
cete
stD
IRI
(ng/
ml)
Mo
nth
2107
——
9.93
24.0
2G
luco
seto
lera
nce
test
DIR
I(n
g/m
l)Se
aso
n21
07—
—4.
8517
.02
Glu
cose
tole
ran
cete
stD
IRI
(ng/
ml)
Sex
2107
——
7.48
20.0
5G
luco
seto
lera
nce
test
DIR
I(n
g/m
l)W
eigh
t21
076.
661.
06—
—G
luco
seto
lera
nce
test
DIR
I/D
GC
age
den
sity
1984
——
6.53
10.8
5
(con
tin
ued
)
Gene–Environment Effects in Mice 975
AP
PE
ND
IX
(Co
nti
nu
ed)
Mai
nef
fect
sIn
tera
ctio
ns
Tes
tP
hen
oty
pe
Co
vari
ate
No
.o
bse
rved
log
P%
vari
ance
exp
lain
edlo
gP
%va
rian
ceex
pla
ined
Glu
cose
tole
ran
cete
stD
IRI/
DG
Lit
ter
1972
——
6.95
9.39
Glu
cose
tole
ran
cete
stD
IRI/
DG
Mo
nth
1984
4.86
1.71
11.1
728
.02
Glu
cose
tole
ran
cete
stD
IRI/
DG
Seas
on
1984
——
6.05
21.7
3G
luco
seto
lera
nce
test
DIR
I/D
GSe
x19
84—
—6.
7419
.65
Glu
cose
tole
ran
cete
stG
luco
se0
(mg/
dl)
Age
2225
4.66
0.43
22.8
11.
50G
luco
seto
lera
nce
test
Glu
cose
0(m
g/d
l)C
age
den
sity
2225
4.71
0.43
18.0
012
.92
Glu
cose
tole
ran
cete
stG
luco
se0
(mg/
dl)
Exp
erim
ente
r22
2523
.96
2.95
24.0
434
.21
Glu
cose
tole
ran
cete
stG
luco
se0
(mg/
dl)
Ho
ur
2225
——
12.9
522
.62
Glu
cose
tole
ran
cete
stG
luco
se0
(mg/
dl)
Lit
ter
2212
13.6
31.
3819
.37
19.7
1G
luco
seto
lera
nce
test
Glu
cose
0(m
g/d
l)M
on
th22
258.
091.
4246
.92
41.4
1G
luco
seto
lera
nce
test
Glu
cose
0(m
g/d
l)Se
aso
n22
255.
890.
7226
.62
39.0
4G
luco
seto
lera
nce
test
Glu
cose
0(m
g/d
l)Se
x22
2515
8.57
20.4
216
.37
24.8
2G
luco
seto
lera
nce
test
Glu
cose
0(m
g/d
l)St
ud
yd
ay22
2514
.64
1.51
24.4
90.
01G
luco
seto
lera
nce
test
Glu
cose
0(m
g/d
l)W
eigh
t22
25—
—15
.79
0.72
Glu
cose
tole
ran
cete
stG
luco
se0
(mg/
dl)
Year
2225
28.2
93.
0910
.67
30.4
0G
luco
seto
lera
nce
test
Glu
cose
15(m
g/d
l)A
ge22
04—
—11
.08
1.30
Glu
cose
tole
ran
cete
stG
luco
se15
(mg/
dl)
Cag
ed
ensi
ty22
04—
—15
.31
18.0
4G
luco
seto
lera
nce
test
Glu
cose
15(m
g/d
l)E
xper
imen
ter
2204
53.7
08.
4316
.69
30.8
2G
luco
seto
lera
nce
test
Glu
cose
15(m
g/d
l)H
ou
r22
045.
291.
166.
0219
.58
Glu
cose
tole
ran
cete
stG
luco
se15
(mg/
dl)
Lit
ter
2192
8.02
1.12
9.18
15.0
6G
luco
seto
lera
nce
test
Glu
cose
15(m
g/d
l)M
on
th22
044.
721.
4031
.77
44.5
5G
luco
seto
lera
nce
test
Glu
cose
15(m
g/d
l)Se
aso
n22
045.
540.
9619
.27
40.9
0G
luco
seto
lera
nce
test
Glu
cose
15(m
g/d
l)Se
x22
0415
.01
2.21
7.35
21.4
0G
luco
seto
lera
nce
test
Glu
cose
15(m
g/d
l)St
ud
yd
ay22
044.
790.
6318
.57
0.01
Glu
cose
tole
ran
cete
stG
luco
se15
(mg/
dl)
Wei
ght
2204
——
5.56
0.55
Glu
cose
tole
ran
cete
stG
luco
se15
(mg/
dl)
Year
2204
12.4
91.
825.
7436
.94
Glu
cose
tole
ran
cete
stG
luco
se30
(mg/
dl)
Age
2187
——
6.94
0.94
Glu
cose
tole
ran
cete
stG
luco
se30
(mg/
dl)
Cag
ed
ensi
ty21
87—
—11
.78
16.1
4G
luco
seto
lera
nce
test
Glu
cose
30(m
g/d
l)E
xper
imen
ter
2187
21.2
34.
0411
.68
29.4
1G
luco
seto
lera
nce
test
Glu
cose
30(m
g/d
l)H
ou
r21
87—
—5.
5920
.08
Glu
cose
tole
ran
cete
stG
luco
se30
(mg/
dl)
Lit
ter
2174
4.68
0.67
8.05
11.0
2G
luco
seto
lera
nce
test
Glu
cose
30(m
g/d
l)M
on
th21
875.
031.
5919
.07
34.3
5G
luco
seto
lera
nce
test
Glu
cose
30(m
g/d
l)Se
aso
n21
875.
721.
0811
.18
31.2
7G
luco
seto
lera
nce
test
Glu
cose
30(m
g/d
l)Se
x21
879.
871.
534.
8418
.00
Glu
cose
tole
ran
cete
stG
luco
se30
(mg/
dl)
Stu
dy
day
2187
——
10.3
30.
01G
luco
seto
lera
nce
test
Glu
cose
30(m
g/d
l)W
eigh
t21
87—
—5.
300.
63G
luco
seto
lera
nce
test
Glu
cose
30(m
g/d
l)Ye
ar21
87—
—4.
7935
.33
Glu
cose
tole
ran
cete
stG
luco
se75
(mg/
dl)
Age
2153
——
7.87
1.02
Glu
cose
tole
ran
cete
stG
luco
se75
(mg/
dl)
Cag
ed
ensi
ty21
53—
—4.
997.
52 (con
tin
ued
)
976 W. Valdar et al.
AP
PE
ND
IX
(Co
nti
nu
ed)
Mai
nef
fect
sIn
tera
ctio
ns
Tes
tP
hen
oty
pe
Co
vari
ate
No
.o
bse
rved
log
P%
vari
ance
exp
lain
edlo
gP
%va
rian
ceex
pla
ined
Glu
cose
tole
ran
cete
stG
luco
se75
(mg/
dl)
Exp
erim
ente
r21
5310
.63
2.14
17.7
437
.77
Glu
cose
tole
ran
cete
stG
luco
se75
(mg/
dl)
Ho
ur
2153
——
7.83
20.6
7G
luco
seto
lera
nce
test
Glu
cose
75(m
g/d
l)L
itte
r21
40—
—10
.28
10.0
5G
luco
seto
lera
nce
test
Glu
cose
75(m
g/d
l)M
on
th21
535.
901.
7018
.07
32.9
7G
luco
seto
lera
nce
test
Glu
cose
75(m
g/d
l)Se
aso
n21
537.
511.
337.
8323
.33
Glu
cose
tole
ran
cete
stG
luco
se75
(mg/
dl)
Sex
2153
34.8
75.
675.
2415
.93
Glu
cose
tole
ran
cete
stG
luco
se75
(mg/
dl)
Stu
dy
day
2153
——
6.82
0.01
Glu
cose
tole
ran
cete
stG
luco
se75
(mg/
dl)
Wei
ght
2153
——
9.78
0.69
Glu
cose
tole
ran
cete
stIn
suli
n0
(ng/
ml)
Cag
ed
ensi
ty22
06—
—11
.14
14.5
2G
luco
seto
lera
nce
test
Insu
lin
0(n
g/m
l)E
xper
imen
ter
2206
——
12.1
928
.49
Glu
cose
tole
ran
cete
stIn
suli
n0
(ng/
ml)
Ho
ur
2206
——
11.0
232
.11
Glu
cose
tole
ran
cete
stIn
suli
n0
(ng/
ml)
Lit
ter
2193
——
9.26
15.0
6G
luco
seto
lera
nce
test
Insu
lin
0(n
g/m
l)M
on
th22
0611
.67
2.91
26.5
642
.42
Glu
cose
tole
ran
cete
stIn
suli
n0
(ng/
ml)
Seas
on
2206
7.28
1.37
15.2
834
.80
Glu
cose
tole
ran
cete
stIn
suli
n0
(ng/
ml)
Sex
2206
12.7
82.
059.
0624
.42
Glu
cose
tole
ran
cete
stIn
suli
n0
(ng/
ml)
Wei
ght
2206
5.08
0.74
——
Glu
cose
tole
ran
cete
stIn
suli
n15
(ng/
ml)
Cag
ed
ensi
ty21
97—
—6.
4410
.52
Glu
cose
tole
ran
cete
stIn
suli
n15
(ng/
ml)
Exp
erim
ente
r21
97—
—7.
7320
.84
Glu
cose
tole
ran
cete
stIn
suli
n15
(ng/
ml)
Lit
ter
2185
——
9.16
10.5
3G
luco
seto
lera
nce
test
Insu
lin
15(n
g/m
l)M
on
th21
978.
962.
3713
.45
27.7
8G
luco
seto
lera
nce
test
Insu
lin
15(n
g/m
l)Se
aso
n21
975.
951.
126.
0320
.13
Glu
cose
tole
ran
cete
stIn
suli
n15
(ng/
ml)
Sex
2197
——
7.91
20.7
3G
luco
seto
lera
nce
test
Insu
lin
15(n
g/m
l)W
eigh
t21
974.
960.
725.
710.
57G
luco
seto
lera
nce
test
Insu
lin
30(n
g/m
l)C
age
den
sity
2178
——
6.23
9.10
Glu
cose
tole
ran
cete
stIn
suli
n30
(ng/
ml)
Exp
erim
ente
r21
78—
—5.
5116
.19
Glu
cose
tole
ran
cete
stIn
suli
n30
(ng/
ml)
Lit
ter
2166
——
7.56
9.10
Glu
cose
tole
ran
cete
stIn
suli
n30
(ng/
ml)
Mo
nth
2178
7.05
2.03
14.1
829
.40
Glu
cose
tole
ran
cete
stIn
suli
n30
(ng/
ml)
Seas
on
2178
——
8.50
24.7
1G
luco
seto
lera
nce
test
Insu
lin
30(n
g/m
l)Se
x21
78—
—7.
2318
.84
Glu
cose
tole
ran
cete
stIn
suli
n30
(ng/
ml)
Wei
ght
2178
4.62
0.67
——
Glu
cose
tole
ran
cete
stIn
suli
n75
(ng/
ml)
Cag
ed
ensi
ty21
124.
880.
707.
159.
48G
luco
seto
lera
nce
test
Insu
lin
75(n
g/m
l)E
xper
imen
ter
2112
——
5.65
17.0
4G
luco
seto
lera
nce
test
Insu
lin
75(n
g/m
l)H
ou
r21
12—
—8.
5522
.87
Glu
cose
tole
ran
cete
stIn
suli
n75
(ng/
ml)
Lit
ter
2100
——
6.11
12.6
0G
luco
seto
lera
nce
test
Insu
lin
75(n
g/m
l)M
on
th21
126.
861.
9616
.98
30.6
6G
luco
seto
lera
nce
test
Insu
lin
75(n
g/m
l)Se
aso
n21
12—
—6.
9121
.29
Glu
cose
tole
ran
cete
stIn
suli
n75
(ng/
ml)
Sex
2112
30.7
65.
187.
8518
.15
Glu
cose
tole
ran
cete
stIn
suli
n75
(ng/
ml)
Wei
ght
2112
11.8
51.
87—
—G
luco
seto
lera
nce
test
Insu
lin
slo
pe
Sex
1122
5.58
1.83
—— (c
onti
nu
ed)
Gene–Environment Effects in Mice 977
AP
PE
ND
IX
(Co
nti
nu
ed)
Mai
nef
fect
sIn
tera
ctio
ns
Tes
tP
hen
oty
pe
Co
vari
ate
No
.o
bse
rved
log
P%
vari
ance
exp
lain
edlo
gP
%va
rian
ceex
pla
ined
Glu
cose
tole
ran
cete
stK
(glu
cose
slo
pe)
Sex
1953
11.1
92.
22—
—G
luco
seto
lera
nce
test
K(g
luco
sesl
op
e)Ye
ar19
534.
830.
87—
—G
row
thG
row
thsl
op
eC
age
den
sity
2418
——
20.0
015
.53
Gro
wth
Gro
wth
slo
pe
Lit
ter
2462
——
26.0
520
.10
Gro
wth
Gro
wth
slo
pe
Sex
2474
135.
7217
.45
19.1
426
.19
Hem
ato
logy
Hem
ogl
ob
in(g
/d
l)M
on
th18
70—
—8.
5923
.95
Hem
ato
logy
Hem
ogl
ob
in(g
/d
l)Se
aso
n18
70—
—5.
0618
.96
Hem
ato
logy
Hem
ogl
ob
in(g
/d
l)Se
x18
709.
071.
73—
—H
emat
olo
gyH
emo
glo
bin
(g/
dl)
Wei
ght
1870
6.22
1.14
4.86
0.40
Hem
ato
logy
Lym
ph
ocy
tes
Age
1833
4.58
0.70
——
Hem
ato
logy
Lym
ph
ocy
tes
Lit
ter
1822
7.18
1.15
7.79
8.82
Hem
ato
logy
Lym
ph
ocy
tes
Mo
nth
1833
——
10.7
225
.40
Hem
ato
logy
Lym
ph
ocy
tes
Seas
on
1833
——
10.2
425
.19
Hem
ato
logy
Lym
ph
ocy
tes
Sex
1833
——
5.90
18.7
1H
emat
olo
gyL
ymp
ho
cyte
sSt
ud
yd
ay18
3314
.16
2.40
——
Hem
ato
logy
Lym
ph
ocy
tes
Year
1833
6.04
0.96
——
Hem
ato
logy
Mea
nce
llu
lar
Hb
con
cen
trat
ion
(%)
Age
1863
9.85
1.40
26.0
41.
83H
emat
olo
gyM
ean
cell
ula
rH
bco
nce
ntr
atio
n(%
)C
age
den
sity
1862
——
33.5
229
.32
Hem
ato
logy
Mea
nce
llu
lar
Hb
con
cen
trat
ion
(%)
Lit
ter
1852
——
39.3
135
.19
Hem
ato
logy
Mea
nce
llu
lar
Hb
con
cen
trat
ion
(%)
Mo
nth
1863
68.9
211
.39
58.1
954
.51
Hem
ato
logy
Mea
nce
llu
lar
Hb
con
cen
trat
ion
(%)
Seas
on
1863
28.1
44.
5440
.00
58.5
8H
emat
olo
gyM
ean
cell
ula
rH
bco
nce
ntr
atio
n(%
)Se
x18
636.
020.
8419
.55
39.1
6H
emat
olo
gyM
ean
cell
ula
rH
bco
nce
ntr
atio
n(%
)St
ud
yd
ay18
635.
960.
8219
.79
0.07
Hem
ato
logy
Mea
nce
llu
lar
Hb
con
cen
trat
ion
(%)
Wei
ght
1863
——
14.6
80.
92H
emat
olo
gyM
ean
cell
ula
rH
bco
nce
ntr
atio
n(%
)Ye
ar18
63—
—31
.10
82.9
4H
emat
olo
gyM
ean
cell
ula
rvo
lum
e(fl
)C
age
den
sity
1875
——
7.63
12.4
7H
emat
olo
gyM
ean
cell
ula
rvo
lum
e(fl
)L
itte
r18
65—
—4.
685.
79H
emat
olo
gyM
ean
cell
ula
rvo
lum
e(fl
)M
on
th18
7613
.39
3.18
15.6
330
.61
Hem
ato
logy
Mea
nce
llu
lar
volu
me
(fl)
Seas
on
1876
——
7.50
21.5
6H
emat
olo
gyM
ean
cell
ula
rvo
lum
e(fl
)Se
x18
76—
—8.
8920
.90
Hem
ato
logy
Mea
nce
llu
lar
volu
me
(fl)
Stu
dy
day
1876
6.15
0.90
——
Hem
ato
logy
Mea
nce
llu
lar
volu
me
(fl)
Wei
ght
1876
——
5.16
0.45
Hem
ato
logy
Mea
nce
llu
lar
volu
me
(fl)
Year
1876
6.67
0.99
——
Hem
ato
logy
Mea
nco
rpu
scu
lar
hem
ogl
ob
in(p
g)A
ge18
71—
—15
.80
1.25
Hem
ato
logy
Mea
nco
rpu
scu
lar
hem
ogl
ob
in(p
g)C
age
den
sity
1870
——
13.3
016
.26
Hem
ato
logy
Mea
nco
rpu
scu
lar
hem
ogl
ob
in(p
g)L
itte
r18
60—
—16
.42
16.5
1H
emat
olo
gyM
ean
corp
usc
ula
rh
emo
glo
bin
(pg)
Mo
nth
1871
32.6
86.
7710
.21
22.9
1H
emat
olo
gyM
ean
corp
usc
ula
rh
emo
glo
bin
(pg)
Seas
on
1871
19.9
43.
628.
8525
.86
Hem
ato
logy
Mea
nco
rpu
scu
lar
hem
ogl
ob
in(p
g)Se
x18
71—
—11
.35
27.4
4
(con
tin
ued
)
978 W. Valdar et al.
AP
PE
ND
IX
(Co
nti
nu
ed)
Mai
nef
fect
sIn
tera
ctio
ns
Tes
tP
hen
oty
pe
Co
vari
ate
No
.o
bse
rved
log
P%
vari
ance
exp
lain
edlo
gP
%va
rian
ceex
pla
ined
Hem
ato
logy
Mea
nco
rpu
scu
lar
hem
ogl
ob
in(p
g)St
ud
yd
ay18
71—
—9.
470.
04H
emat
olo
gyM
ean
corp
usc
ula
rh
emo
glo
bin
(pg)
Wei
ght
1871
——
5.59
0.55
Hem
ato
logy
Mea
nco
rpu
scu
lar
hem
ogl
ob
in(p
g)Ye
ar18
71—
—8.
5244
.24
Hem
ato
logy
Pla
tele
tcri
t(%
)A
ge18
39—
—5.
100.
73H
emat
olo
gyP
late
letc
rit
(%)
Mo
nth
1839
14.3
94.
066.
2619
.33
Hem
ato
logy
Pla
tele
tcri
t(%
)Se
aso
n18
394.
851.
114.
5919
.65
Hem
ato
logy
Pla
tele
tcri
t(%
)Se
x18
3936
.50
7.50
8.92
27.5
3H
emat
olo
gyP
late
lets
(n/
ml)
Mo
nth
1863
16.4
34.
1810
.19
24.8
1H
emat
olo
gyP
late
lets
(n/
ml)
Seas
on
1863
6.62
1.36
7.75
26.6
4H
emat
olo
gyP
late
lets
(n/
ml)
Sex
1863
30.9
25.
7610
.78
27.6
7H
emat
olo
gyP
late
lets
(n/
ml)
Stu
dy
day
1863
9.44
1.60
——
Hem
ato
logy
Pla
tele
ts(n
/m
l)W
eigh
t18
635.
770.
935.
540.
50H
emat
olo
gyP
late
lets
(n/
ml)
Year
1863
5.56
0.89
——
Hem
ato
logy
Red
blo
od
cell
cou
nt
(n/
ml)
Mo
nth
1870
——
11.8
829
.98
Hem
ato
logy
Red
blo
od
cell
cou
nt
(n/
ml)
Seas
on
1870
——
5.84
21.5
2H
emat
olo
gyR
edb
loo
dce
llco
un
t(n
/m
l)Se
x18
709.
321.
774.
9519
.31
Hem
ato
logy
Red
blo
od
cell
cou
nt
(n/
ml)
Wei
ght
1870
5.90
1.07
4.94
0.48
Hem
ato
logy
Red
cell
dis
trib
uti
on
wid
thL
itte
r18
50—
—4.
648.
40H
emat
olo
gyR
edce
lld
istr
ibu
tio
nw
idth
Mo
nth
1861
8.27
2.18
10.6
823
.56
Hem
ato
logy
Red
cell
dis
trib
uti
on
wid
thSe
aso
n18
61—
—5.
7417
.99
Hem
ato
logy
Red
cell
dis
trib
uti
on
wid
thSe
x18
6112
.88
1.99
——
Hem
ato
logy
Red
cell
dis
trib
uti
on
wid
thW
eigh
t18
61—
—4.
860.
42H
emat
olo
gyW
hit
eb
loo
dce
llco
un
t(n
/m
l)C
age
den
sity
1875
——
5.44
12.8
8H
emat
olo
gyW
hit
eb
loo
dce
llco
un
t(n
/m
l)L
itte
r18
656.
241.
0011
.57
12.5
4H
emat
olo
gyW
hit
eb
loo
dce
llco
un
t(n
/m
l)M
on
th18
76—
—15
.14
33.4
6H
emat
olo
gyW
hit
eb
loo
dce
llco
un
t(n
/m
l)Se
aso
n18
76—
—15
.64
36.7
7H
emat
olo
gyW
hit
eb
loo
dce
llco
un
t(n
/m
l)Se
x18
76—
—6.
8923
.62
Hem
ato
logy
Wh
ite
blo
od
cell
cou
nt
(n/
ml)
Stu
dy
day
1876
10.1
81.
716.
860.
03H
emat
olo
gyW
hit
eb
loo
dce
llco
un
t( n
/m
l)W
eigh
t18
76—
—5.
480.
58H
emat
olo
gyW
hit
eb
loo
dce
llco
un
t(n
/m
l)Ye
ar18
76—
—6.
3342
.86
Hem
ato
logy
Hem
ato
crit
(%)
Mo
nth
1873
——
10.1
327
.26
Hem
ato
logy
Hem
ato
crit
(%)
Seas
on
1873
——
4.92
19.3
1H
emat
olo
gyH
emat
ocr
it(%
)Se
x18
7312
.18
2.39
5.01
18.4
1H
emat
olo
gyH
emat
ocr
it(%
)W
eigh
t18
735.
591.
026.
600.
48Im
mu
no
logy
%B
2201
Age
1723
——
9.73
2.70
Imm
un
olo
gy%
B22
01C
age
den
sity
1677
——
7.72
10.4
9Im
mu
no
logy
%B
2201
Lit
ter
1713
——
9.38
14.2
6Im
mu
no
logy
%B
2201
Mo
nth
1723
11.6
82.
8428
.30
41.2
8Im
mu
no
logy
%B
2201
Seas
on
1723
——
23.9
946
.06
(con
tin
ued
)
Gene–Environment Effects in Mice 979
AP
PE
ND
IX
(Co
nti
nu
ed)
Mai
nef
fect
sIn
tera
ctio
ns
Tes
tP
hen
oty
pe
Co
vari
ate
No
.o
bse
rved
log
P%
vari
ance
exp
lain
edlo
gP
%va
rian
ceex
pla
ined
Imm
un
olo
gy%
B22
01
Sex
1723
13.0
22.
0710
.71
28.8
1Im
mu
no
logy
%C
D31
Lit
ter
1723
5.00
0.78
6.68
13.1
9Im
mu
no
logy
%C
D31
Mo
nth
1733
16.6
54.
0719
.89
37.1
7Im
mu
no
logy
%C
D31
Seas
on
1733
5.47
1.12
14.6
935
.98
Imm
un
olo
gy%
CD
31
Sex
1733
——
11.5
730
.57
Imm
un
olo
gy%
CD
41
Cag
ed
ensi
ty16
73—
—4.
928.
94Im
mu
no
logy
%C
D41
Lit
ter
1721
——
11.4
218
.10
Imm
un
olo
gy%
CD
41
Mo
nth
1731
14.9
93.
9423
.00
44.6
4Im
mu
no
logy
%C
D41
Seas
on
1731
——
18.1
644
.24
Imm
un
olo
gy%
CD
41
Sex
1731
——
9.74
28.8
8Im
mu
no
logy
%C
D41
/C
D31
Age
1732
——
6.12
1.24
Imm
un
olo
gy%
CD
41
/C
D31
Cag
ed
ensi
ty16
74—
—5.
406.
88Im
mu
no
logy
%C
D41
/C
D31
Lit
ter
1722
——
15.8
110
.27
Imm
un
olo
gy%
CD
41
/C
D31
Mo
nth
1732
25.7
14.
6513
.23
21.8
2Im
mu
no
logy
%C
D41
/C
D31
Seas
on
1732
8.50
1.35
8.04
17.8
9Im
mu
no
logy
%C
D81
Age
1733
——
5.32
1.08
Imm
un
olo
gy%
CD
81
Mo
nth
1733
14.1
72.
577.
5714
.65
Imm
un
olo
gy%
CD
81
Seas
on
1733
10.5
31.
46—
—Im
mu
no
logy
%C
D81
Sex
1733
——
5.30
12.6
1Im
mu
no
logy
%N
Kce
lls
Cag
ed
ensi
ty16
67—
—5.
2910
.41
Imm
un
olo
gy%
NK
cell
sL
itte
r17
14—
—11
.43
16.7
9Im
mu
no
logy
%N
Kce
lls
Mo
nth
1724
35.2
78.
6816
.15
32.9
1Im
mu
no
logy
%N
Kce
lls
Seas
on
1724
9.04
2.06
16.0
437
.88
Imm
un
olo
gy%
NK
cell
sSe
x17
245.
220.
95—
—Im
mu
no
logy
CD
41/
CD
81A
ge17
29—
—6.
021.
07Im
mu
no
logy
CD
41/
CD
81C
age
den
sity
1671
——
4.85
5.83
Imm
un
olo
gyC
D41
/C
D81
Lit
ter
1719
——
10.6
27.
45Im
mu
no
logy
CD
41/
CD
81M
on
th17
2917
.55
3.26
9.38
17.3
9Im
mu
no
logy
CD
41
/C
D81
Seas
on
1729
8.52
1.29
4.78
12.2
1L
engt
hB
od
yle
ngt
h(c
m)
Age
1942
——
7.56
0.81
Len
gth
Bo
dy
len
gth
(cm
)L
itte
r19
32—
—10
.25
8.30
Len
gth
Bo
dy
len
gth
(cm
)M
on
th19
4216
.46
3.22
11.2
921
.08
Len
gth
Bo
dy
len
gth
(cm
)Se
aso
n19
425.
610.
9113
.42
24.6
9L
engt
hB
od
yle
ngt
h(c
m)
Sex
1942
35.1
25.
17—
—L
engt
hB
od
yle
ngt
h(c
m)
Stu
dy
day
1942
——
4.91
0.02
Len
gth
Bo
dy
len
gth
(cm
)W
eigh
t19
4287
.23
13.9
4—
—L
engt
hB
od
yle
ngt
h(c
m)
Year
1942
5.94
0.76
——
New
ho
me-
cage
acti
vity
Fin
em
ove
men
tA
ge22
945.
140.
72—
—N
ewh
om
e-ca
geac
tivi
tyF
ine
mo
vem
ent
Sex
2294
7.62
1.13
—— (c
onti
nu
ed)
980 W. Valdar et al.
AP
PE
ND
IX
(Co
nti
nu
ed)
Mai
nef
fect
sIn
tera
ctio
ns
Tes
tP
hen
oty
pe
Co
vari
ate
No
.o
bse
rved
log
P%
vari
ance
exp
lain
edlo
gP
%va
rian
ceex
pla
ined
New
ho
me-
cage
acti
vity
To
tal
bea
mb
reak
s(3
0m
in)
Exp
erim
ente
r22
90—
—6.
4917
.79
New
ho
me-
cage
acti
vity
To
tal
bea
mb
reak
s(3
0m
in)
Mo
nth
2290
——
7.05
18.2
2N
ewh
om
e-ca
geac
tivi
tyT
ota
lb
eam
bre
aks
(30
min
)Se
aso
n22
90—
—4.
8716
.40
New
ho
me-
cage
acti
vity
To
tal
bea
mb
reak
s(fi
rst
5m
in)
Exp
erim
ente
r22
8911
.94
2.90
5.06
15.5
0N
ewh
om
e-ca
geac
tivi
tyT
ota
lb
eam
bre
aks
(firs
t5
min
)M
on
th22
89—
—11
.44
24.5
3N
ewh
om
e-ca
geac
tivi
tyT
ota
lb
eam
bre
aks
(firs
t5
min
)Se
aso
n22
89—
—9.
4923
.45
New
ho
me-
cage
acti
vity
To
tal
bea
mb
reak
s(l
ast
5m
in)
Ho
ur
2275
4.99
1.41
——
Op
enfi
eld
Fec
alb
oli
Mo
nth
2304
5.34
1.75
——
Op
enfi
eld
Fec
alb
oli
Sex
2304
——
5.40
16.3
8O
pen
fiel
dT
ota
lac
tivi
tyE
xper
imen
ter
2302
4.99
1.34
——
Op
enfi
eld
To
tal
acti
vity
Seas
on
2302
——
6.11
16.9
6O
pen
fiel
dT
ota
lac
tivi
tySe
x23
027.
601.
07—
—P
leth
ysm
ogr
aph
yE
nh
ance
dp
ause
(bas
elin
e)A
ge21
69—
—15
.55
2.18
Ple
thys
mo
grap
hy
En
han
ced
pau
se(b
asel
ine)
Cag
ed
ensi
ty21
69—
—7.
428.
81P
leth
ysm
ogr
aph
yE
nh
ance
dp
ause
(bas
elin
e)H
ou
r21
69—
—18
.39
31.9
6P
leth
ysm
ogr
aph
yE
nh
ance
dp
ause
(bas
elin
e)L
itte
r21
576.
970.
9124
.63
25.4
5P
leth
ysm
ogr
aph
yE
nh
ance
dp
ause
(bas
elin
e)M
on
th21
6977
.44
11.8
724
.29
31.4
3P
leth
ysm
ogr
aph
yE
nh
ance
dp
ause
(bas
elin
e)Se
aso
n21
6948
.57
7.17
13.7
127
.43
Ple
thys
mo
grap
hy
En
han
ced
pau
se(b
asel
ine)
Sex
2169
15.8
02.
2411
.77
25.3
8P
leth
ysm
ogr
aph
yE
nh
ance
dp
ause
(bas
elin
e)St
ud
yd
ay21
69—
—20
.59
0.09
Ple
thys
mo
grap
hy
En
han
ced
pau
se(b
asel
ine)
Year
2169
5.51
0.72
12.0
848
.49
Ple
thys
mo
grap
hy
En
han
ced
pau
se(m
etac
ho
lin
e)A
ge19
43—
—7.
641.
41P
leth
ysm
ogr
aph
yE
nh
ance
dp
ause
(met
ach
oli
ne)
Ho
ur
1943
——
20.3
736
.68
Ple
thys
mo
grap
hy
En
han
ced
pau
se(m
etac
ho
lin
e)L
itte
r19
31—
—10
.94
20.8
6P
leth
ysm
ogr
aph
yE
nh
ance
dp
ause
(met
ach
oli
ne)
Mo
nth
1943
16.7
23.
7619
.83
37.1
3P
leth
ysm
ogr
aph
yE
nh
ance
dp
ause
(met
ach
oli
ne)
Seas
on
1943
11.8
72.
1215
.67
36.3
1P
leth
ysm
ogr
aph
yE
nh
ance
dp
ause
(met
ach
oli
ne)
Sex
1943
21.6
33.
569.
8426
.78
Ple
thys
mo
grap
hy
En
han
ced
pau
se(m
etac
ho
lin
e)W
eigh
t19
436.
510.
97—
—P
leth
ysm
ogr
aph
yE
nh
ance
dp
ause
(met
ach
oli
ne)
Year
1943
——
8.18
50.3
9P
leth
ysm
ogr
aph
yE
xpir
ato
ryti
me
(bas
elin
e)H
ou
r21
65—
—17
.65
34.3
8P
leth
ysm
ogr
aph
yE
xpir
ato
ryti
me
(bas
elin
e)L
itte
r21
53—
—9.
0910
.52
Ple
thys
mo
grap
hy
Exp
irat
ory
tim
e(b
asel
ine)
Mo
nth
2165
17.7
23.
9411
.84
26.4
1P
leth
ysm
ogr
aph
yE
xpir
ato
ryti
me
(bas
elin
e)Se
aso
n21
6513
.74
2.42
10.1
426
.77
Ple
thys
mo
grap
hy
Exp
irat
ory
tim
e(b
asel
ine)
Sex
2165
——
9.43
25.6
0P
leth
ysm
ogr
aph
yE
xpir
ato
ryti
me
(bas
elin
e)St
ud
yd
ay21
65—
—5.
300.
03P
leth
ysm
ogr
aph
yE
xpir
ato
ryti
me
(bas
elin
e)W
eigh
t21
654.
770.
686.
660.
57P
leth
ysm
ogr
aph
yE
xpir
ato
ryti
me
(bas
elin
e)Ye
ar21
659.
981.
53—
—P
leth
ysm
ogr
aph
yE
xpir
ato
ryti
me
(met
ach
oli
ne)
Ho
ur
1935
——
5.56
15.7
5P
leth
ysm
ogr
aph
yE
xpir
ato
ryti
me
(met
ach
oli
ne)
Mo
nth
1935
5.31
1.78
—— (c
onti
nu
ed)
Gene–Environment Effects in Mice 981
AP
PE
ND
IX
(Co
nti
nu
ed)
Mai
nef
fect
sIn
tera
ctio
ns
Tes
tP
hen
oty
pe
Co
vari
ate
No
.o
bse
rved
log
P%
vari
ance
exp
lain
edlo
gP
%va
rian
ceex
pla
ined
Ple
thys
mo
grap
hy
Exp
irat
ory
tim
e(m
etac
ho
lin
e)Se
x19
35—
—6.
1517
.12
Ple
thys
mo
grap
hy
Insp
irat
ory
tim
e(b
asel
ine)
Cag
ed
ensi
ty21
745.
180.
74—
—P
leth
ysm
ogr
aph
yIn
spir
ato
ryti
me
(bas
elin
e)H
ou
r21
74—
—17
.02
32.0
9P
leth
ysm
ogr
aph
yIn
spir
ato
ryti
me
(bas
elin
e)L
itte
r21
62—
—12
.07
12.8
7P
leth
ysm
ogr
aph
yIn
spir
ato
ryti
me
(bas
elin
e)M
on
th21
7415
.47
3.57
9.87
24.2
8P
leth
ysm
ogr
aph
yIn
spir
ato
ryti
me
(bas
elin
e)Se
aso
n21
7410
.83
1.95
10.0
927
.17
Ple
thys
mo
grap
hy
Insp
irat
ory
tim
e(b
asel
ine)
Sex
2174
12.3
21.
9512
.50
29.6
1P
leth
ysm
ogr
aph
yIn
spir
ato
ryti
me
(bas
elin
e)St
ud
yd
ay21
74—
—4.
990.
03P
leth
ysm
ogr
aph
yIn
spir
ato
ryti
me
(bas
elin
e)W
eigh
t21
74—
—9.
220.
71P
leth
ysm
ogr
aph
yIn
spir
ato
ryti
me
(met
ach
oli
ne)
Ho
ur
1946
——
7.07
18.9
8P
leth
ysm
ogr
aph
yIn
spir
ato
ryti
me
(met
ach
oli
ne)
Mo
nth
1946
5.41
1.64
——
Ple
thys
mo
grap
hy
Insp
irat
ory
tim
e(m
etac
ho
lin
e)Se
aso
n19
464.
580.
86—
—P
leth
ysm
ogr
aph
yIn
spir
ato
ryti
me
(met
ach
oli
ne)
Sex
1946
20.6
43.
33—
—P
leth
ysm
ogr
aph
yIn
spir
ato
ryti
me
(met
ach
oli
ne)
Wei
ght
1946
6.35
0.93
——
Ple
thys
mo
grap
hy
Pen
Hd
iffe
ren
ceA
ge19
34—
—7.
341.
63P
leth
ysm
ogr
aph
yP
enH
dif
fere
nce
Cag
ed
ensi
ty19
34—
—5.
679.
31P
leth
ysm
ogr
aph
yP
enH
dif
fere
nce
Ho
ur
1934
——
19.0
835
.57
Ple
thys
mo
grap
hy
Pen
Hd
iffe
ren
ceL
itte
r19
22—
—9.
5318
.03
Ple
thys
mo
grap
hy
Pen
Hd
iffe
ren
ceM
on
th19
348.
202.
3221
.79
42.7
5P
leth
ysm
ogr
aph
yP
enH
dif
fere
nce
Seas
on
1934
5.00
1.00
17.3
542
.74
Ple
thys
mo
grap
hy
Pen
Hd
iffe
ren
ceSe
x19
3414
.92
2.52
12.0
229
.38
Ple
thys
mo
grap
hy
Pen
Hd
iffe
ren
ceW
eigh
t19
34—
—6.
270.
60P
leth
ysm
ogr
aph
yP
enH
dif
fere
nce
Year
1934
——
10.7
258
.13
Ple
thys
mo
grap
hy
Res
pir
ato
ryra
te(b
asel
ine)
Cag
ed
ensi
ty21
634.
820.
69—
—P
leth
ysm
ogr
aph
yR
esp
irat
ory
rate
(bas
elin
e)H
ou
r21
63—
—18
.19
33.5
0P
leth
ysm
ogr
aph
yR
esp
irat
ory
rate
(bas
elin
e)L
itte
r21
51—
—11
.93
12.5
3P
leth
ysm
ogr
aph
yR
esp
irat
ory
rate
(bas
elin
e)M
on
th21
6321
.39
4.60
10.4
024
.62
Ple
thys
mo
grap
hy
Res
pir
ato
ryra
te(b
asel
ine)
Seas
on
2163
16.1
42.
849.
6526
.40
Ple
thys
mo
grap
hy
Res
pir
ato
ryra
te(b
asel
ine)
Sex
2163
6.22
0.92
11.0
127
.80
Ple
thys
mo
grap
hy
Res
pir
ato
ryra
te(b
asel
ine)
Stu
dy
day
2163
——
6.20
0.04
Ple
thys
mo
grap
hy
Res
pir
ato
ryra
te(b
asel
ine)
Wei
ght
2163
——
6.07
0.57
Ple
thys
mo
grap
hy
Res
pir
ato
ryra
te(b
asel
ine)
Year
2163
6.34
0.94
——
Ple
thys
mo
grap
hy
Res
pir
ato
ryra
te(m
etac
ho
lin
e)H
ou
r19
28—
—5.
8717
.38
Ple
thys
mo
grap
hy
Res
pir
ato
ryra
te(m
etac
ho
lin
e)Se
aso
n19
285.
211.
08—
—P
leth
ysm
ogr
aph
yT
idal
min
ute
volu
me
(bas
elin
e)A
ge21
58—
—5.
040.
68P
leth
ysm
ogr
aph
yT
idal
min
ute
volu
me
(bas
elin
e)C
age
den
sity
2158
7.51
0.89
——
Ple
thys
mo
grap
hy
Tid
alm
inu
tevo
lum
e(b
asel
ine)
Ho
ur
2158
——
11.5
419
.48
Ple
thys
mo
grap
hy
Tid
alm
inu
tevo
lum
e(b
asel
ine)
Lit
ter
2146
——
6.21
7.69
Ple
thys
mo
grap
hy
Tid
alm
inu
tevo
lum
e(b
asel
ine)
Mo
nth
2158
13.4
92.
5412
.97
20.2
8
(con
tin
ued
)
982 W. Valdar et al.
AP
PE
ND
IX
(Co
nti
nu
ed)
Mai
nef
fect
sIn
tera
ctio
ns
Tes
tP
hen
oty
pe
Co
vari
ate
No
.o
bse
rved
log
P%
vari
ance
exp
lain
edlo
gP
%va
rian
ceex
pla
ined
Ple
thys
mo
grap
hy
Tid
alm
inu
tevo
lum
e(b
asel
ine)
Seas
on
2158
——
8.70
19.4
1P
leth
ysm
ogr
aph
yT
idal
min
ute
volu
me
(bas
elin
e)Se
x21
5864
.43
9.12
——
Ple
thys
mo
grap
hy
Tid
alm
inu
tevo
lum
e(b
asel
ine)
Wei
ght
2158
68.9
09.
81—
—P
leth
ysm
ogr
aph
yT
idal
min
ute
volu
me
(met
ach
oli
ne)
Ho
ur
1930
——
6.17
11.8
1P
leth
ysm
ogr
aph
yT
idal
min
ute
volu
me
(met
ach
oli
ne)
Lit
ter
1918
——
5.61
5.33
Ple
thys
mo
grap
hy
Tid
alm
inu
tevo
lum
e(m
etac
ho
lin
e)M
on
th19
3018
.51
3.03
4.64
10.6
0P
leth
ysm
ogr
aph
yT
idal
min
ute
volu
me
(met
ach
oli
ne)
Seas
on
1930
10.8
11.
45—
—P
leth
ysm
ogr
aph
yT
idal
min
ute
volu
me
(met
ach
oli
ne)
Sex
1930
105.
0514
.76
5.95
12.0
0P
leth
ysm
ogr
aph
yT
idal
min
ute
volu
me
(met
ach
oli
ne)
Wei
ght
1930
71.2
59.
555.
820.
35P
leth
ysm
ogr
aph
yT
idal
volu
me
(bas
elin
e)A
ge21
49—
—16
.84
1.43
Ple
thys
mo
grap
hy
Tid
alvo
lum
e(b
asel
ine)
Cag
ed
ensi
ty21
49—
—6.
014.
08P
leth
ysm
ogr
aph
yT
idal
volu
me
(bas
elin
e)H
ou
r21
49—
—20
.24
22.3
2P
leth
ysm
ogr
aph
yT
idal
volu
me
(bas
elin
e)L
itte
r21
37—
—16
.96
16.0
6P
leth
ysm
ogr
aph
yT
idal
volu
me
(bas
elin
e)M
on
th21
4939
.79
5.07
20.3
222
.38
Ple
thys
mo
grap
hy
Tid
alvo
lum
e(b
asel
ine)
Seas
on
2149
20.9
02.
4110
.96
20.8
7P
leth
ysm
ogr
aph
yT
idal
volu
me
(bas
elin
e)Se
x21
4913
1.89
16.9
87.
7513
.06
Ple
thys
mo
grap
hy
Tid
alvo
lum
e(b
asel
ine)
Stu
dy
day
2149
——
7.27
0.03
Ple
thys
mo
grap
hy
Tid
alvo
lum
e(b
asel
ine)
Wei
ght
2149
87.9
410
.73
6.12
0.32
Ple
thys
mo
grap
hy
Tid
alvo
lum
e(m
etac
ho
lin
e)A
ge19
32—
—9.
740.
80P
leth
ysm
ogr
aph
yT
idal
volu
me
(met
ach
oli
ne)
Ho
ur
1932
——
10.7
215
.83
Ple
thys
mo
grap
hy
Tid
alvo
lum
e(m
etac
ho
lin
e)L
itte
r19
20—
—8.
867.
08P
leth
ysm
ogr
aph
yT
idal
volu
me
(met
ach
oli
ne)
Mo
nth
1932
26.8
13.
645.
2210
.32
Ple
thys
mo
grap
hy
Tid
alvo
lum
e(m
etac
ho
lin
e)Se
aso
n19
3218
.02
2.07
——
Ple
thys
mo
grap
hy
Tid
alvo
lum
e(m
etac
ho
lin
e)Se
x19
3214
1.45
18.4
36.
0311
.35
Ple
thys
mo
grap
hy
Tid
alvo
lum
e(m
etac
ho
lin
e)W
eigh
t19
3285
.28
10.3
0—
—P
leth
ysm
ogr
aph
yT
idal
volu
me
(met
ach
oli
ne)
Year
1932
6.15
0.59
——
Wei
ght
Bo
dy
mas
sin
dex
Age
1925
5.87
0.79
——
Wei
ght
Bo
dy
mas
sin
dex
Mo
nth
1925
8.83
2.16
7.41
16.7
5W
eigh
tB
od
ym
ass
ind
exSe
aso
n19
256.
211.
079.
9321
.20
Wei
ght
Bo
dy
mas
sin
dex
Sex
1925
113.
9320
.32
——
Wei
ght
Bo
dy
mas
sin
dex
Wei
ght
1925
19.9
13.
03—
—W
eigh
tW
eigh
t,10
wk
(g)
Cag
ed
ensi
ty23
19—
—5.
373.
29W
eigh
tW
eigh
t,10
wk
(g)
Lit
ter
2307
——
10.2
76.
10W
eigh
tW
eigh
t,10
wk
(g)
Sex
2320
Inf
41.3
7—
—W
eigh
tW
eigh
t,6
wk
(g)
Cag
ed
ensi
ty24
325.
570.
3220
.89
9.30
Wei
ght
Wei
ght,
6w
k(g
)L
itte
r24
98—
—39
.27
16.6
9W
eigh
tW
eigh
t,6
wk
(g)
Sex
2511
Inf
30.6
312
.63
12.8
7W
eigh
tW
eigh
t,7
wk
(g)
Cag
ed
ensi
ty24
055.
040.
268.
224.
40W
eigh
tW
eigh
t,7
wk
(g)
Lit
ter
2457
6.16
0.32
21.1
17.
79 (con
tin
ued
)
Gene–Environment Effects in Mice 983
AP
PE
ND
IX
(Co
nti
nu
ed)
Mai
nef
fect
sIn
tera
ctio
ns
Tes
tP
hen
oty
pe
Co
vari
ate
No
.o
bse
rved
log
P%
vari
ance
exp
lain
edlo
gP
%va
rian
ceex
pla
ined
Wei
ght
Wei
ght,
7w
k(g
)Se
x24
70In
f35
.40
7.13
8.27
Wei
ght
Wei
ght,
8w
k(g
)L
itte
r22
90—
—10
.46
2.53
Wei
ght
Wei
ght,
8w
k(g
)Se
x23
02In
f44
.52
——
Wo
un
dh
eali
ng
Ear
ho
lear
ea(m
m2)
Cag
ed
ensi
ty21
8510
.45
1.37
9.10
9.56
Wo
un
dh
eali
ng
Ear
ho
lear
ea(m
m2)
Lit
ter
2172
6.00
0.76
9.72
10.5
9W
ou
nd
hea
lin
gE
arh
ole
area
(mm
2)
Mo
nth
2185
24.1
74.
349.
9418
.33
Wo
un
dh
eali
ng
Ear
ho
lear
ea(m
m2)
Seas
on
2185
17.8
12.
676.
0814
.33
Wo
un
dh
eali
ng
Ear
ho
lear
ea(m
m2)
Sex
2185
13.9
31.
914.
8712
.85
Wo
un
dh
eali
ng
Ear
ho
lear
ea(m
m2)
Stu
dy
day
2185
——
9.67
0.04
Wo
un
dh
eali
ng
Ear
ho
lear
ea(m
m2)
Year
2185
——
6.42
32.6
4
No
teth
atn
ot
allc
om
bin
atio
ns
of
ph
eno
typ
ean
dco
vari
ate
wer
eav
aila
ble
inth
est
ud
y.L
og
Pd
eno
tes
the
loga
rith
mto
the
bas
e10
of
the
P-v
alu
e.In
fd
eno
tes
aP
-val
ue
that
was
com
pu
tati
on
ally
ind
isti
ngu
ish
able
fro
mze
ro.
Fo
rb
revi
ty,
resu
lts
are
om
itte
dfo
ref
fect
sw
ith
log
P’s
of
,4.
55(i
.e.,
the
corr
ecte
d5%
sign
ifica
nce
leve
l).
984 W. Valdar et al.