Susceptibility to infection such as SARS-CoV-2 may be influenced by host genotype. TwinsUK volunteers (n = 3261) completing the C-19 COVID-19 symptom tracker app allowed classical twin studies of COVID-19 symptoms, including predicted COVID-19, a symptom-based algorithm to predict true infection, derived from app users tested for SARS-CoV-2. We found heritability of 49% (32−64%) for delirium; 34% (20−47%) for diarrhea; 31% (8−52%) for fatigue; 19% (0−38%) for anosmia; 46% (31−60%) for skipped meals and 31% (11−48%) for predicted COVID-19. Heritability estimates were not affected by cohabiting or by social deprivation. The results suggest the importance of host genetics in the risk of clinical manifestations of COVID-19 and provide grounds for planning genome-wide association studies to establish specific genes involved in viral infectivity and the host immune response.

A healthy diet is associated with the improvement or maintenance of health parameters, and several indices have been proposed to assess diet quality comprehensively. Twin studies have found that some specific foods, nutrients and food patterns have a heritable component; however, the heritability of overall dietary intake has not yet been estimated. Here, we compute heritability estimates of the nine most common dietary indices utilized in nutritional epidemiology. We analyzed 2590 female twins from TwinsUK (653 monozygotic [MZ] and 642 dizygotic [DZ] pairs) who completed a 131-item food frequency questionnaire (FFQ). Heritability estimates were computed using structural equation models (SEM) adjusting for body mass index (BMI), smoking status, Index of Multiple Deprivation (IMD), physical activity, menopausal status, energy and alcohol intake. The AE model was the best-fitting model for most of the analyzed dietary scores (seven out of nine), with heritability estimates ranging from 10.1% (95% CI [.02, .18]) for the Dietary Reference Values (DRV) to 42.7% (95% CI [.36, .49]) for the Alternative Healthy Eating Index (A-HEI). The ACE model was the best-fitting model for the Healthy Diet Indicator (HDI) and Healthy Eating Index 2010 (HEI-2010) with heritability estimates of 5.4% (95% CI [−.17, .28]) and 25.4% (95% CI [.05, .46]), respectively. Here, we find that all analyzed dietary indices have a heritable component, suggesting that there is a genetic predisposition regulating what you eat. Future studies should explore genes underlying dietary indices to further understand the genetic disposition toward diet-related health parameters.

CVD is the leading cause of death worldwide and, after dementia, is the second biggest cause of death for women. In England, it accounts for one in four of all deaths. Lifestyle modifications represent the primary route both to reduce CVD risk factors and prevent CVD outcomes. Diet constitutes one of the key modifiable risk factors in the aetiology of CVD. We investigated the relationship between nine main dietary indices and a comprehensive range of CVD risk factors in 2590 women from TwinsUK. After adjustment for multiple testing, we found that the Dietary Approaches to Stop Hypertension (DASH) diet was inversely correlated with some of the most common CVD risk factors (BMI, visceral fat (VF), TAG, insulin, homoeostasis model assessment of insulin resistance (HOMA2-IR) and atherosclerotic CVD (ASCVD) risk) with PFDR ranging from 6·28 × 10−7 to 5·63 × 10−4. Similar association patterns were detected across most of the dietary indices analysed. In our post hoc investigation, to determine if any specific food groups were driving associations between the DASH score and markers of cardiometabolic risk, we found that increased BMI, VF, HOMA2-IR, ASCVD risk, insulin and TAG levels were directly correlated with red meat consumption (PFDR ranging from 4·65 × 10−9 to 7·98 × 10−3) and inversely correlated with whole-grain cereal consumption (PFDR ranging from 1·26 × 10−6 to 8·28 × 10−3). Our findings revealed that the DASH diet is associated with a more favourable CVD risk profile, suggesting that this diet may be a candidate dietary pattern to supplement current UK dietary recommendations for CVD prevention.

Glycemic, insulinemic and lipemic postprandial responses are multi-factorial and contribute to diabetes, obesity and CVD. The aim of the PREDICT I study is to assess the genetic, metabolic, metagenomic, and meal-context contribution to postprandial responses, integrating the metabolic burden and gut microbiome to predict individual responses to food using a machine learning algorithm.

A multi-center postprandial study of 1,000 individuals from the UK (unrelated, identical and non-identical twins) and 100 unrelated individuals from the US, assessed postprandial (0–6h) metabolic responses to sequential mixed-nutrient dietary challenges (50 g fat and 85 g carbohydrate at 0 h; 22 g fat and 71 g carbohydrate at 4h) in a clinic setting. Glycemic responses to 5 duplicate isocaloric meals of different macronutrient content and self-selected meals (> 100,000), were tested at home using a continuous glucose monitor (CGM). Baseline factors included metabolomics, genomics, gut metagenomics and body composition. Genetic contributions to postprandial responses were determined by classical twin methods.

Inter-individual variability in postprandial responses (glucose, insulin and triacylglycerol (TG)) was high in the clinic setting: iAUC IQR (median) was (n = 644); glucose (0–2h) 1.97 (1.89) mmol/L.h, insulin (0–2h) 45.6 (67.7) mIU/L.h and TG (0–6h) 2.37 (2.42) mmol/L.h. The unadjusted genetic contribution for glucose, insulin and TG responses were 54%, 29% and 27% respectively. Within-individual concordance (ICC) in glucose responses (iAUC 0–2h) for at home duplicate isocaloric meals was moderate-to-high, depending on the test meal: ICC (95%CI) was; high carbohydrate 0.62 (0.58,0.66), (carbohydrate = 95g/76% energy; n = 764), average lunch 0.57 (0.53, 0.62) (carbohydrate = 68g/54% energy; n = 763), OGTT 0.65 (0.61,0.70) (carbohydrate = 75 g; n = 754), high fat 0.35 (0.28, 0.41) (fat = 40g/71% energy; n = 576) and high protein 0.56, (0.48,0.62) (protein = 41g/32% energy; n = 364). An interim machine learning algorithm predicted 46% of the variation in glycemic responses based on meal content, meal context and participant's baseline characteristics, excluding genetic and microbiome features. Only 29% of variation could be explained by the macronutrient content of the meal.

This is the most comprehensive postprandial study performed to date. The large and modifiable variation in metabolic responses to identical meals in healthy people explains why ‘one size fits all’ nutritional guidelines are problematic. The genetic component to these responses is moderate, leaving the majority of the variation potentially modifiable. By collecting information on glucose responses to > 100,000 meals, alongside environmental, genetic and microbiome variables, we will have excellent power to use machine learning to optimise and predict individual responses to foods.

Postprandial lipemia is an independent risk factor for CVD, due to effects on lipoprotein remodelling, oxidative stress, inflammation, haemostasis and endothelial dysfunction. However, it is unknown whether the total, peak or duration of the lipemic response determines risk. The PREDICT I study is the largest study to date to measure postprandial lipemic responses and intermediary acutely changing cardiometabolic risk factors at multiple time points using a standardized test meal model.

A multi-center postprandial study of 1,000 individuals from the UK (unrelated, identical and non-identical twins) and 100 unrelated individuals from the US, assessed postprandial (hourly 0–6h) metabolic responses to sequential mixed-nutrient dietary challenges (50 g fat, 85 g carbohydrate at 0 h; 22 g fat, 71 g carbohydrate at 4h) in a clinic setting. We investigated the relationship of different postprandial triacylglycerol (TG) measures (4 and 6 h TG iAUC, 4 and 6 h TG concentration, 4 and 6 h TG increase from fasting) with lipoprotein remodelling (XXL-VLDL (including chylomicron remnants and VLDL particles) and XL-VLDL particle concentrations (average diameters > 75, 64 nm respectively), HDL-C) and levels of glycosylated acute phase proteins (GlycA; marker of cardiovascular inflammation), all of which have been implicated as independent predictors of CVD risk.

Following adjustment (for use of medication, demographic characteristics, fasting TG, insulin and glucose levels), all six postprandial TG measures (4 and 6 h TG iAUC, 4 and 6 h TG concentration, 4 and 6 h TG increase from fasting) were strongly correlated with markers of atherogenic lipoprotein remodelling and the marker of cardiovascular inflammation (GlycA). The strongest correlation (interim analysis) was observed for the 6 h TG increase from fasting (all P < 0.001, Pearson's coefficient r = 0.94 [95%CI's; 0.93, 0.95] for XXL-VLDL-P; r = 0.95 [95%CI's; 0.95, 0.96] for XL-VLDL-P; r = 0.89 [95%CI's; 0.88, 0.91] for GlycA ; r = -0.61 [95%CI's; -0.66, -0.55] for HDL-C). Inter-individual variability in postprandial lipemic responses was high in the tightly controlled clinic setting (interim analysis, n = 656); IQR (median) was; iAUC (0–6h) 2.39 (2.31) mmol/L.h; Cmax 1.32 (2.06) mmol/L; Tmax 30.0 (300) min; and increase above fasting at 6 h 0.78 (0.62) mmol/L.

This is the most detailed postprandial study performed to date and suggests that identifying predictors of the postprandial 6 h TG rise will have the highest CVD relevance. Ongoing exploration in PREDICT I of the determinants of postprandial lipemic responses considering environmental, genetic and microbiome variables will significantly advance our ability to predict an individual's postprandial response and its links to cardiovascular risk.

Twin researchers face the challenge of accurately determining the zygosity of twins for research. As part of the annual questionnaire between 1999 and 2006, 8,307 twins from the TwinsUK registry were asked to complete five questions (independently from their co-twin) to ascertain their self-perceived zygosity during childhood on up to five separate occasions. This questionnaire is known as the ‘peas in the pod’ questionnaire (PPQ), but there is little evidence of its validation. Answers were scored and classified as monozygotic (MZ), dizygotic (DZ), or unknown zygosity (UZ) and were compared with 4,484 twins with genotyping data who had not been selected for zygosity. Of these, 3,859 individuals (46.5% of those who had a zygosity from PPQ) had zygosity classified by both the PPQ and genotyping. Of the 708 individual twins whose answers meant that they were consistently classed as MZ in the PPQ, 683 (96.5%) were MZ within the genotype data. Of the 945 individual twins consistently classed as DZ within questionnaire, 936 (99.0%) were DZ in the genotype data. Where both twins scored MZ consistently across multiple questionnaires, 99.6% were MZ on genotyping, 99.7% were DZ on genotyping if both twins consistently scored DZ. However, for the initial questionnaire, 88.6% of those scoring as MZ were genotypically MZ and 98.7% DZ. For twin pairs where both scored UZ, 94.7% were DZ. Using the PPQ on a single occasion provided a definitive classification of whether the twin was MZ or DZ with an overall accuracy of 86.9%, increasing to 97.9% when there was a consistent classification of zygosity across multiple questionnaires. This study has shown that the PPQ questionnaire is an excellent proxy indicator of zygosity in the absence of genotyping information.

Twin pairs discordant for disease may help elucidate the epigenetic mechanisms and causal environmental factors in disease development and progression. To obtain the numbers of pairs, especially monozygotic (MZ) twin pairs, necessary for in-depth studies while also allowing for replication, twin studies worldwide need to pool their resources. The Discordant Twin (DISCOTWIN) consortium was established for this goal. Here, we describe the DISCOTWIN Consortium and present an analysis of type 2 diabetes (T2D) data in nearly 35,000 twin pairs. Seven twin cohorts from Europe (Denmark, Finland, Norway, the Netherlands, Spain, Sweden, and the United Kingdom) and one from Australia investigated the rate of discordance for T2D in same-sex twin pairs aged 45 years and older. Data were available for 34,166 same-sex twin pairs, of which 13,970 were MZ, with T2D diagnosis based on self-reported diagnosis and medication use, fasting glucose and insulin measures, or medical records. The prevalence of T2D ranged from 2.6% to 12.3% across the cohorts depending on age, body mass index (BMI), and national diabetes prevalence. T2D discordance rate was lower for MZ (5.1%, range 2.9–11.2%) than for same-sex dizygotic (DZ) (8.0%, range 4.9–13.5%) pairs. Across DISCOTWIN, 720 discordant MZ pairs were identified. Except for the oldest of the Danish cohorts (mean age 79), heritability estimates based on contingency tables were moderate to high (0.47–0.77). From a meta-analysis of all data, the heritability was estimated at 72% (95% confidence interval 61–78%). This study demonstrated high T2D prevalence and high heritability for T2D liability across twin cohorts. Therefore, the number of discordant MZ pairs for T2D is limited. By combining national resources, the DISCOTWIN Consortium maximizes the number of discordant MZ pairs needed for in-depth genotyping, multi-omics, and phenotyping studies, which may provide unique insights into the pathways linking genes to the development of many diseases.

Low birth weight (LBW) can have an impact on health outcomes in later life, especially in relation to pre-disposition to metabolic disease. Several studies suggest that LBW resulting from restricted intrauterine growth leaves a footprint on DNA methylation in utero, and this influence likely persists into adulthood. To investigate this further, we performed epigenome-wide association analyses of blood DNA methylation using Infinium HumanMethylation450 BeadChip profiles in 71 adult monozygotic (MZ) twin pairs who were extremely discordant for birth weight. A signal mapping to the IGF1R gene (cg12562232, p = 2.62 × 10−8), was significantly associated with birth weight discordance at a genome-wide false-discovery rate (FDR) of 0.05. We pursued replication in three additional independent datasets of birth weight discordant MZ pairs and observed the same direction of association, but the results were not significant. However, a meta-analysis across the four independent samples, in total 216 birth-weight discordant MZ twin pairs, showed a significant positive association between birth weight and DNA methylation differences at IGF1R (random-effects meta-analysis p = .04), and the effect was particularly pronounced in older twins (random-effects meta-analysis p = .008, 98 older birth-weight discordant MZ twin pairs). The results suggest that severe intra-uterine growth differences (birth weight discordance >20%) are associated with methylation changes in the IGF1R gene in adulthood, independent of genetic effects.

Food liking-disliking patterns may strongly influence food choices and health. Here we assess: (1) whether food preference patterns are genetic/environmentally driven; and (2) the relationship between metabolomics profiles and food preference patterns in a large population of twins. 2,107 individuals from TwinsUK completed an online food and lifestyle preference questionnaire. Principle components analysis was undertaken to identify patterns of food liking-disliking. Heritability estimates for each liking pattern were obtained by structural equation modeling. The correlation between blood metabolomics profiles (280 metabolites) and each food liking pattern was assessed in a subset of 1,491 individuals and replicated in an independent subset of monozygotic twin pairs discordant for the liking pattern (65 to 88 pairs). Results from both analyses were meta-analyzed. Four major food-liking patterns were identified (Fruit and Vegetable, Distinctive Tastes, Sweet and High Carbohydrate, and Meat) accounting for 26% of the total variance. All patterns were moderately heritable (Fruit and Vegetable, h2[95% CI]: 0.36 [0.28; 0.44]; Distinctive Tastes: 0.58 [0.52; 0.64]; Sweet and High Carbohydrate: 0.52 [0.45, 0.59] and Meat: 0.44 [0.35; 0.51]), indicating genetic factors influence food liking-disliking. Overall, we identified 14 significant metabolite associations (Bonferroni p < 4.5 × 10−5) with Distinctive Tastes (8 metabolites), Sweet and High Carbohydrate (3 metabolites), and Meat (3 metabolites). Food preferences follow patterns based on similar taste and nutrient characteristics and these groupings are strongly determined by genetics. Food preferences that are strongly genetically determined (h2 ≥ 0.40), such as for meat and distinctive-tasting foods, may influence intakes more substantially, as demonstrated by the metabolomic associations identified here.

Investigations into the genetic architecture of diet–disease relationships are particularly relevant today with the global epidemic of obesity and chronic disease. Twin studies have demonstrated that genetic makeup plays a significant role in a multitude of dietary phenotypes such as energy and macronutrient intakes, dietary patterns, and specific food group intakes. Besides estimating heritability of dietary assessment, twins provide a naturally unique, case–control experiment. Due to their shared upbringing, matched genes and sex (in the case of monozygotic (MZ) twin pairs), and age, twins provide many advantages over classic epidemiological approaches. Future genetic epidemiological studies could benefit from the twin approach particularly where defining what is ‘normal’ is problematic due to the high inter-individual variability underlying metabolism. Here, we discuss the use of twins to generate heritability estimates of food intake phenotypes. We then highlight the value of discordant MZ pairs to further nutrition research through discovery and validation of biomarkers of intake and health status in collaboration with cutting-edge omics technologies.

Low weight at birth has previously been shown to be associated with a number of adult diseases such as type 2 diabetes, cardiovascular disease, high blood pressure, and obesity later in life. Genome-wide association studies (GWAS) have been published for singleton-born individuals, but the role of genetic variation in birth weight (BW) in twins has not yet been fully investigated. A GWAS was performed in 4,593 female study participants with BW data available from the TwinsUK cohort. A genome-wide significant signal was found in chromosome 9, close to the NTRK2 gene (OMIM: 600456). QIMR, an Australian twin cohort (n = 3,003), and UK-based singleton-birth individuals from the Hertfordshire cohort (n = 2,997) were used as replication for the top two single nucleotide polymorphism (SNPs) underpinning this signal, rs12340987 and rs7849941. The top SNP, rs12340987, was found to be in the same direction in the Australian twins and in the singleton-born females (fixed effects meta-analysis beta = -0.13, SE = 0.02, and p = 1.48 × 10−8) but not in the singleton-born males tested. These findings provide an important insight into the genetic component of BW in twins who are normally excluded due to their lower BW when compared with singleton births, as well as the difference in BW between twins. The NTRK2 gene identified in this study has previously been associated with obesity.

Genome-wide association analysis on monozygotic twin-pairs offers a route to discovery of gene–environment interactions through testing for variability loci associated with sensitivity to individual environment/lifestyle. We present a genome-wide scan of loci associated with intra-pair differences in serum lipid and apolipoprotein levels. We report data for 1,720 monozygotic female twin-pairs from GenomEUtwin project with 2.5 million SNPs, imputed or genotyped, and measured serum lipid fractions for both twins. We found one locus associated with intra-pair differences in high-density lipoprotein cholesterol, rs2483058 in an intron of SRGAP2, where twins carrying the C allele are more sensitive to environmental factors (P = 3.98 × 10−8). We followed up the association in further genotyped monozygotic twins (N = 1,261), which showed a moderate association for the variant (P = 0.200, same direction of an effect). In addition, we report a new association on the level of apolipoprotein A-II (P = 4.03 × 10−8).

Although the co-occurrence among symptoms of insomnia, fatigue, and depression has been frequently reported, the etiology of this co-occurrence remains poorly understood. A total of 3,758 adult female twins in the United Kingdom completed a mail-out survey including six questions concerning frequency and severity of symptoms of insomnia, fatigue, and depression. Correlations among the scores of the three symptoms ranged from 0.35 to 0.44. Among various multivariate models we tested, the common-pathway model explained the data best. In the best-fitting model, the common factor was explained approximately equally by genetic and unique environmental factors (49% and 51%, respectively). In addition to the common variance, there was a significant specific variance in each symptom, where unique environmental factors were much larger than genetic factors. These results imply that although there are shared genetic liabilities for the development of symptoms of depression, fatigue, and insomnia, it is environmental experiences that make etiological distinctions among three symptoms.

Strabismus represents a complex oculomotor disorder characterized by the deviation of one or both eyes and poor vision. A more sophisticated understanding of the genetic liability of strabismus is required to guide searches for associated molecular variants. In this classical twin study of 1,462 twin pairs, we examined the relative influence of genes and environment in comitant strabismus, and the degree to which these influences can be explained by factors in common with refractive error. Participants were examined for the presence of latent (‘phoria’) and manifest (‘tropia’) strabismus using cover–uncover and alternate cover tests. Two phenotypes were distinguished: eso-deviation (esophoria and esotropia) and exo-deviation (exophoria and exotropia). Structural equation modeling was subsequently employed to partition the observed phenotypic variation in the twin data into specific variance components. The prevalence of eso-deviation and exo-deviation was 8.6% and 20.7%, respectively. For eso-deviation, the polychoric correlation was significantly greater in monozygotic (MZ) (r = 0.65) compared to dizygotic (DZ) twin pairs (r = 0.33), suggesting a genetic role (p = .003). There was no significant difference in polychoric correlation between MZ (r = 0.55) and DZ twin pairs (r = 0.53) for exo-deviation (p = .86), implying that genetic factors do not play a significant role in the etiology of exo-deviation. The heritability of an eso-deviation was 0.64 (95% CI 0.50–0.75). The additive genetic correlation for eso-deviation and refractive error was 0.13 and the bivariate heritability (i.e., shared variance) was less than 1%, suggesting negligible shared genetic effect. This study documents a substantial heritability of 64% for eso-deviation, yet no corresponding heritability for exo-deviation, suggesting that the genetic contribution to strabismus may be specific to eso-deviation. Future studies are now needed to identify the genes associated with eso-deviation and unravel their mechanisms of action.

Association studies, comparing elite athletes with sedentary controls, have reported a number of genes that may be related to athlete status. The present study reports the first genome wide linkage scan for athlete status. Subjects were 4488 adult female twins from the TwinsUK Adult Twin Registry (793 monozygotic [MZ] and 1000 dizygotic [DZ] complete twin pairs, and single twins). Athlete status was measured by asking the twins whether they had ever competed in sports and what was the highest level obtained. Twins who had competed at the county or national level were considered elite athletes. Using structural equation modeling in Mx, the heritability of athlete status was estimated at 66%. Seven hundred DZ twin pairs that were successfully genotyped for 1946 markers (736 microsatellites and 1210 SNPs) were included in the linkage analysis. Identical-by-descent probabilities were estimated in Merlin for a 1 cM grid, taking into account the linkage disequilibrium of correlated SNPs. The linkage scan was carried out in Mx using the -approach. Suggestive linkages were found on chromosomes 3q22-q24 and 4q31-q34. Both areas converge with findings from previous studies using exercise phenotypes. The peak on 3q22-q24 was found at the SLC9A9 gene. The region 4q31-q34 overlaps with the region for which suggestive linkages were found in two previous linkage studies for physical fitness (FABP2 gene; Bouchard et al., 2000) and physical activity (UCP1 gene; Simonen et al., 2003). Future association studies should further clarify the possible role of these genes in athlete status.

One thousand and seventy three pairs of adult monozygotic (MZ) twins and 895 pairs of same sex adult dizygotic (DZ) twins from the United Kingdom (UK) completed the Humor Styles Questionnaire: a 32-item measure which assesses two positive and two negative styles of humor. MZ correlations were approximately twice as large as DZ correlations for all four humor styles, and univariate behavioral genetic model fitting indicated that individual differences in all of them can be accounted for entirely by genetic and nonshared environmental factors, with heritabilities ranging from .34 to .49. These results, while perhaps not surprising, are somewhat at odds with a previous study that we conducted in North America (Vernon et al., in press) in which genetic factors contributed significantly to individual differences in the two positive humor styles, but contributed far less to the two negative styles, variance in which was instead largely due to shared and nonshared environmental factors. We suggest that differences between North American and UK citizens in their appreciation of different kinds of humor may be responsible for the different results obtained in these two studies.

The purpose of the present study was to determine if a general factor of personality (GFP) could be extracted from the six dimensions of the HEXACO model and four factors of trait emotional intelligence. Participants were 1,192 pairs of twins (666 MZ pairs, 526 DZ pairs) between the ages of 19 to 86 years, who completed the Trait Emotional Intelligence Questionnaire — Short Form and the HEXACO Personality Inventory — Revised. Principal components analysis yielded a strong GFP accounting for 33% of the variance, on which all variables with the exception of honesty-humility from the HEXACO showed moderate to large loadings. Behavioral genetic (BG) analyses revealed that individual differences in the GFP were entirely attributable to additive genetic and non-shared environmental factors — results that are in accord with previous BG analyses of a GFP. The present study adds to the body of evidence in support of a heritable GFP but an alternative perspective is also discussed.

The UK Adult Twin Registry was started in 1993 and consists of approximately 10,000 monozygotic (MZ) and dizygotic (DZ) adult Caucasian twins aged 16 to 85 years from all over the United Kingdom, plus some parents and siblings. It now incorporates previous twin registries from the Institute of Psychiatry and Aberdeen University. This is a volunteer sample recruited by successive media campaigns without selecting for particular diseases or traits. All twins receive a series of detailed disease and environmental questionnaires. The majority of twins have been assessed in detail clinically at several time points for several hundred phenotypes related to common diseases or intermediate traits. The focus to date has been primarily in 5 areas — cardiovascular, metabolic, musculoskeletal, ophthalmologic diseases as well as the aging process. Over 3000 DZ twins have had a 10cM genome-wide scan performed and 5000 twins tagged for over 200 candidate genes allowing both linkage and association studies. The resource has led to many successful and innovative research projects particularly in common age-related diseases, and has led to collaborations with over 80 groups worldwide.

In humans, in contrast to animals, the genetic influences on infidelity are unclear. We report here a large study of over 1600 unselected United Kingdom female twin pairs who confidentially reported previous episodes of infidelity and total lifetime number of sexual partners, as well as attitudes towards infidelity. Our findings demonstrate that infidelity and number of sexual partners are both under moderate genetic influence (41% and 38% heritable, respectively) and the genetic correlation between these two traits is strong (47%). Conversely, attitudes towards infidelity are driven by shared and unique environmental, but not genetic, influences. A genome-wide linkage scan identified three suggestive but nonsignificant linkage areas associated with infidelity and number of sexual partners on chromosomes 3, 7 and 20 with a maximum LOD score of 2.46. We were unsuccessful in associating infidelity or number of sexual partners with a locus implicated in other mammals' sexual behavior, the vasopressin receptor gene. Nonetheless, our findings on the heritabil-ity of sexual infidelity and number of sexual partners provide support for certain evolutionary theories of human sexual behavior, as well as justifying further genetic and molecular research in this domain.