Introduction

Salivary (AMY1) and pancreatic (AMY2A) amylase enzymes are responsible for starch digestion, which begins in the oral cavity and continues in the small intestine. The AMY1 and AMY2A genes show extensive copy number (CN) variability in humans, with a reported number of gene copies ranging from 2 to 18 for AMY1, and from 0 to 8 for AMY2A1,2,3,4. It has been shown that CN distribution at the salivary amylase gene is significantly variable between populations, with the number of copies of AMY1 reflecting a biological adaptation to traditionally high-starch or low-starch diets throughout evolution5.

In 2014, we first reported an association between reduced AMY1 CN and increased body mass index (BMI) and obesity risk using 6200 individuals of European and Asian ancestries6, although subsequent studies attempting to replicate this association yielded conflicting results. For instance, association with AMY1 CN was not replicated in 4000 individuals of European ancestry, including people selected for being at the extremes of the BMI distribution3, as well as in a case-control study of 932 Chinese and 145 Malay samples7, and in 1400 participants from the UK 1958 Birth Cohort8. On the other hand, studies specifically analyzing obesity in children and young adults supported the association of BMI with amylase gene copy number in French9, Mexican10, and Italian children11, as well as in females with early-onset obesity from Finland12.

These studies highlight the complexity of studying an endpoint which has both genetic and environmental components, and suggest that differences in ethnicity, environment and food preferences may further influence the manifestation of this complex phenotype in the setting of genetic susceptibility. Indeed, previous works exploring the relationship between AMY1 CN and diet revealed a significant effect of the interaction between AMY1 CN and starch intake on BMI in 4800 nondiabetic adults from Sweden13, and greater weight and central adiposity loss following randomized low-calorie diet interventions among carriers of the allele rs11185098-A (a proxy of higher AMY1 CN and activity3), compared to noncarriers, among 692 Europeans from The POUNDS Lost Trial14. Taken together, these studies suggest that environmental factors, and particularly dietary choices, may play a role in modulating the observed association between AMY1 CN and adiposity.

Here, we report a large-scale association study between CN at the amylase genes (AMY1 and AMY2A) and adiposity traits in a large Middle Eastern cohort. Specifically, we combined CN inference from high-coverage (30×) whole-genome sequencing (WGS) with phenotypic traits related to adiposity traits and behaviors, collected for almost 3000 subjects as part of the Qatar Biobank15. Our findings help explain trans-ethnic differences in the effect of amylase CN on adiposity and introduce a role for subpopulation-specific traditional dietary and lifestyle choices in determining the strength of association between amylase and adiposity in global populations.

Results

Distribution of adiposity traits in the Qatari population

The Qatar Biobank (QBB) collected a wide range of traits, biochemical measurements, and lifestyle questionnaires from adult Qatari nationals and long-term residents15. While many of these traits will be available for future studies, we focused this first analysis of QBB data on adiposity traits, specifically: BMI, total fat percentage, and trunk fat percentage.

Among the 2935 individuals for whom genomic data was available as part of the Qatar Genome Programme (QGP) pilot phase, 1464 were females and 1471 males. Measures of BMI, total and trunk fat percentages were normally distributed with means (SD) of 28.9 (5.7), 32.7 (9.7) and 32.8 (9.1), respectively (Table 1, Fig. 1). Mean age was not statistically different between sex groups (Wilcoxon’s P > 0.05). Conversely, all the adiposity traits under study were significantly higher in female than in male subjects (Table 1, Fig. 1; Wilcoxon’s P < 5.08 × 10−5), with the strongest difference being observed for total fat percentage (Wilcoxon’s P = 1.54 × 10−295).

Table 1 Adiposity traits of 2935 QBB individuals sequenced as part of the QGP pilot phase.
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Fig. 1: Distribution of adiposity traits.
figure 1

Density plots showing BMI, total and trunk fat percentages distribution in the Qatari population (N = 1471 and 1464 females and males, respectively). The mean trait value (µ), stratified by sex, was evaluated by means of the Wilcoxon’s test, and p-values are reported above each panel.

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Range of AMY1 and AMY2A copy number variability in the Qatari population

We first aimed to estimate the range of discrete CN variation at human salivary (AMY1) and pancreatic (AMY2A) amylase genes in the Qatari population by coverage analysis of WGS data from 2935 individuals from the QBB (see “Methods” section).

Following post-mapping quality control of reads from whole-genome sequencing data (see “Methods” section), we found that the percentage of correctly aligned reads ranged from 90 to 97%, for AMY1 (mean = 95.2%, median = 95.3%, interquartile range [IQR] = 94.7–95.8%), and from 90 to 99%, for AMY2A (mean = 94.5%, median = 94.7%, IQR = 94.2–95.0%; Supplementary Fig. 1). In addition, the average per-individual percentage of reads with mapping quality score >20 and uniquely mapping to both AMY1 and AMY2A was 99.99%, corresponding to a probability of inaccurate mapping of at most 0.01 (Supplementary Fig. 1).

In the Qatari population, AMY1 gene copy number ranges from 2 to 22, AMY2A from 0 to 5, and AMY2B from 1 to 5 copies. Consistent with previous reports1,3,6,16, the number of copies of AMY1 and AMY2A were significantly correlated to each other (polychoric correlation estimate ρ = 0.28, P < 2.22 × 10−308; Fig. 2b), with 72% of the Qatari population carrying an even diploid number of AMY1 genes and two copies of AMY2A.

Fig. 2: AMY1 and AMY2A variation in the Qatari population.
figure 2

a Histograms showing the distribution of estimated copy numbers of AMY1 and AMY2A, obtained from coverage analysis of whole-genome sequencing data in all the Qatari population (N = 2935, white), and Arabs (N = 1518, light blue) and Persians (N = 948, dark blue) from Qatar. b In the Qatari population, AMY2A and AMY1 show parity: when AMY2A copy number is odd, so is AMY1 copy number.

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The number of copies of AMY2A and AMY2B showed high correlation (Pearson’s ρ = 0.81, P < 2.22 × 10−308), corresponding to 90% of QBB samples carrying the same number of copies of these two genes. In 88% of the discordant CN calls at AMY2A and AMY2B, AMY2A arbored CN variations, whereas AMY2B was copy-invariable (CN = 2). This is consistent with previous studies reporting 95% of haploid similarity between AMY2A and AMY2B CN2,3, and substantial higher CN variation (24% vs. 10%, respectively) at AMY2A compared to AMY2B2. Due to the extensive overlap between AMY2A and AMY2B CN, and the higher variability observed at the AMY2A locus compared to AMY2B, when these were CN-discordant, AMY2B was excluded from subsequent analyses.

We further investigated the presence of damaging loss-of-function (LoF) variants within the coding region of AMY1 and AMY2A and which may affect the number of active copies of the genes and therefore skew the results (see “Methods” section); however we found no variants with putative disruptive effects (i.e., stop gained, frameshift, splice variants or in-frame deletions). Indeed, the frequency of LoF variants in AMY1 and AMY2A is reported to be rare (MAF < 1%) in the general population based on the Genome Aggregation Database (gnomAD)17.

Validation of amylase copy number estimates

We estimated AMY1 and AMY2A CN on 40 samples using digital droplet PCR (ddPCR; Methods), identifying only six discrepancies with respect to the CNs estimated with the Carpenter et al.’s approach1 used here (five for AMY1 calls and one for AMY2A calls, Supplementary Table 1), therefore confirming a very high accuracy (74/80 = 92.5%) of our calls across both loci. Notably, four out of five instances of discrepancy at AMY1 deviated from the ddPCR results for a single copy, with consequent deviation from shared odd/even parity between AMY1 and AMY2A CN. Such a deviation is reported to have a low frequency in the general population3, and was avoided in our analysis, where conditional rounding was applied.

We used AMYCNE18 to further validate the AMY1 CN inferred using the approach described by Carpenter et al.1 and observed a strong agreement between the two approaches (Pearson’s ρ = 0.98; P < 2.22 × 10−308; N = 2935, Supplementary Fig. 2).

Association of amylase genes CNs with adiposity in the Qatari population

Anthropometric measurements of adiposity (BMI, total fat percentage, and trunk fat percentage) were tested for association with AMY1 and AMY2A CN in 2935 individuals from Qatar using PopPAnTe19, including sex, age at the sample collection, and the first 10 PCs from genome-wide data as covariates (see “Methods” section). At a Bonferroni-adjusted significance threshold of 8.33 × 10−3 (see “Methods” section), AMY1 appeared significantly associated with trunk fat percentage (β = −0.02, SE = 0.01; P = 7.50 × 10−3; Table 2). Conversely, no significant association was observed for AMY2A (P > 0.05; Table 2).

Table 2 Associations between amylase copy number and adiposity traits in the Qatari population.
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Qatari genetic subpopulations

Since the Qatari population includes subjects of different ancestries, we further sought to distinguish them within our sample and assess their contribution to the observed association between AMY1 and adiposity. To identify the underlying genetic ancestries, we performed principal component analysis (PCA) using ancestry informative markers20,21 and identified individuals clustering with three major Qatari subpopulations (namely, Bedouin Arabs, Persians and East Africans; see “Methods” section, Fig. 3). We excluded from further analyses East Africans, because of their small sample size (N = 63), along with admixed individuals (N = 406) which could not be assigned to a majority ethnic ancestry. Persians (N = 948) and Arabs (N = 1518) were thus selected for subsequent study.

Fig. 3: Principal component analysis.
figure 3

Scatterplot of the first two principal components assessed on ancestry-informative SNPs of 2,935 individuals from Qatar (see “Methods” section). Individual data points are color-coded according to previously described major ethnic ancestry: Arabs (red), Persians (light blue), and East Africans (green). Admixed individuals (purple) are those whose majority ancestry cannot be assigned to one group.

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To avoid further demographic confounders, we investigated but did not find differences between the two groups in age (µPersians = 40,3; µArabs = 39.1; Wilcoxon’s P = 0.02) or sex distribution (χ2 P > 0.05). Despite the similar make-up of the two groups, Qataris with Persian ancestry appeared to have an overall healthier adiposity profile than those with Arab ancestry, as measured by BMI (µArabs = 29.25; µPersians = 27.84; Wilcoxon’s P = 1.34 × 10−8), total fat (µArabs = 33.68; µPersians = 31.00; P = 2.1 × 10−10) and trunk fat percentages (µArabs = 33.89; µPersians = 31.02; P = 1.3 × 10−13), all of which were significantly lower in Persians as compared to Arabs (Fig. 4). Furthermore, consistent with the distribution from the overall group, within each ethnic group total and trunk fat percentages were remarkably higher in females than males, though this difference was less pronounced in Persians (Wilcoxon’s PArabs < 4.90 × 10−86; PPersians < 9.18 × 10−33; Fig. 4). Conversely, females were observed to have significantly higher BMI than males (P = 9.90 × 10−7; Fig. 4) only among Arabs.

Fig. 4: Distribution of adiposity traits in Arabs and Persians from Qatar.
figure 4

Boxplots showing BMI, total and trunk fat percentages distribution in Arabs (N = 1518, gray) and Persians (N = 948, blue). The center line of the boxplots indicates the median, limits of the box indicate the 25th and 75th percentile. The whiskers represent either 1.5 times the interquartile range (IQR) or the maximum/minimum data point if they are within 1.5 times the IQR. The mean trait value (µ) stratified by ethnic group and the p-values, evaluated by means of the Wilcoxon’s test, are reported above each panel. Sex-stratified p-value within each ethnic group are reported within each panel.

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AMY1 and AMY2A CNs are higher in Qataris with Persian ancestry

AMY1 and AMY2A CNs showed significant correlations in both Arabs and Persians (polychoric correlation estimate ρArabs = 0.27, P = 4.57 × 10−315; ρPersians = 0.29, P = 1.91 × 10−201; Fig. 2b), with 75 and 65% of the Arab and Persian subpopulation, respectively, carrying an even number of AMY1 genes and two copies of AMY2A.

We observed significant differences in CN distribution at AMY1 and AMY2A between Persians and Arabs (χ2 test P = 7.23 × 10−12 and P = 9.15 × 10−21, respectively), with Persian subjects appearing to have alleles with a higher number of copies of AMY1 (µArabs = 6.92 copies; µPersians = 7.60 copies; Wilcoxon’s test P = 1.32 × 10−10; Fig. 2a), as well as AMY2A (µArabs = 2.06; µPersians = 2.27; Wilcoxon’s test P = 7.49 × 10−21; Fig. 2a).

Differences in AMY1 and AMY2A CNs distribution between Arabs and Persian were supported by differences in estimated haplotypes frequencies at both loci (Supplementary Methods; Supplementary Results, Supplementary Fig. 3).

Genetic ancestry at the AMY1 locus

To rule out the possibility that the amylase locus may not reflect the overall genetic ancestry assigned to each individual based on genome-wide markers, we performed a further PCA using SNPs and indels located within a 5-MB window surrounding AMY1 (see “Methods” section). Our analysis confirmed that individuals of Arab and Persian ancestry were still well separated in this novel principal component space (Supplementary Fig. 4), while also highlighting the presence of a small subset of outliers (NArabs = 75, NPersians = 34), likely reflecting finer ancestry substructures within these main ancestry groups. Notably, we investigated whether the exclusion of these individuals would influence the association signals identified in our primary analysis, and found negligible differences (see “Methods” section, Supplementary Table 2).

Association between AMY1 CN and adiposity traits in Arabs and Persians

Total fat percentage, BMI, and trunk fat percentage were tested for association with AMY1 CN in 948 Persians and 1518 Arabs from Qatar using PopPAnTe19. Sex and age at sample collection were included as covariates, as well as the first 10 PCs from genome-wide data (see “Methods” section).

At a Bonferroni-adjusted significance threshold of 8.33 × 10−3 (see “Methods” section), we observed negative associations between AMY1 CNs and both total and trunk fat percentages in Arabs (P < 4.60 × 10−3; Table 3, Fig. 5). In addition, lower AMY1 CNs was nominally associated with increased BMI in Arabs (P = 8.40 × 10−3). Conversely, no significant association (P > 0.05) was observed in Persians; however, the direction of association of AMY1 with adiposity was concordant between ethnic groups (Table 3).

Table 3 Associations between AMY1 copy number and adiposity traits in Persians and Arabs from Qatar.
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Fig. 5: AMY1 CN association with adiposity in Arabs from Qatar.
figure 5

The scatter plots depict the correlation between salivary amylase copy number (x-axis) and sex-corrected and age-corrected measures of adiposity (y-axis). Pearson’s correlation coefficients (ρ) and p-values are reported above each panel.

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In addition, case-control analysis of 593 obese (BMI ≥ 30 kg/m2) and 357 normal weight (BMI < 25 kg/m2) Arab individuals from the same dataset highlighted that higher AMY1 CN was indeed inversely associated with obesity risk (OR = 0.93, 95% CI = [0.88–0.98]; P = 0.01).

Contribution of population specific behaviors to AMY1 association with adiposity

Both AMY1 copy number variability and its contribution to adiposity are thought to arise as a product of the adaptive interaction between AMY1 and environmental exposure to starch throughout evolution5. As a consequence, it is prudent to consider that diverse ancestral environments and differences in lifestyle choices (e.g., dietary behavior) may have impacted AMY1 CNVs association with adiposity in Persian and Arab Qataris.

Among study subjects, 1805 individuals (1148 Arabs and 657 Persians) were overweight or obese (BMI ≥ 25 kg/m2). Notably, in reviewing the QBB intake questionnaires, we found that 1013 of these declared to have modified their diet during the year of data collection because of excess weight and its related comorbidities (e.g., high cholesterol, hypertension, and diabetes). Furthermore, we observed by multiple logistic regression (see “Methods” section) a significant difference between Arabs and Persians in the tendency towards dietary self-restraint following weight gain, with 54 and 60% of overweight or obese Arabs and Persians restraining their diet, respectively (P = 4.29 × 10−5). In the same analysis, sex also appeared to be a significant (P = 1.36 × 10−6) determinant of dietary behaviors in overweight or obese subjects from Qatar, with 60% of overweight females (58 and 65% in Arabs and Persians, respectively) displaying dietary restraint, as compared to only 52% of overweight males (49 and 56% in Arabs and Persians, respectively). Interestingly, higher AMY1 copy number was negatively associated with diet restraint in overweight subjects (OR per estimated unit copy increase = 0.94, 95% CI = 0.91–0.98; P = 3.22 × 10−3).

Effect of ethnicity on the association between AMY1 and adiposity traits and on dietary restraint

It could be hypothesized that if AMY1 CN segregates with ancestry, such that increased Arab ancestry corresponds to decreased AMY1 CN, and at the same time genetic factors other than AMY1 increase the risk of adiposity in Arabs, such that increased Arab ancestry corresponds to increased adiposity, then these two independent events would generate a spurious association between AMY1 CN and adiposity traits. To investigate this further, we explored the relationship between varying degrees of ancestry, as defined using the first principal component (PC1) values (see “Methods” section) and both AMY1 CN and adiposity traits.

After accounting for age and sex, adiposity traits showed significant negative associations with PC1 among both individuals of Arab ancestry (β = −4.66, SE = 2.47, P = 0.06; β = −4.85, SE = 1.79, P = 6.88 × 10−3; β = −6.31, SE = 2.12, P = 3.02 × 10−3, for BMI, total and trunk fat and total fat percentages, respectively) and Persian ancestry (β = −18.53, SE = 6.18, P = 2.77 × 10−3; β = −14.27, SE = 4.75, P = 2.73 × 10−3; β = −18.90, SE = 5.79, P = 1.13 × 10−3, for BMI, total and trunk fat and total fat percentages, respectively; Supplementary Fig. 5). Conversely, AMY1 CN did not associate with PC1 in Persians (P = 0.23), and only weakly in Arabs (β = −13.57, SE = 6.57, P = 0.04; Supplementary Fig. 5), where an increased Arab ancestry actually associated with higher copy number, i.e., in the opposite direction compared to our original association results. Therefore, our main findings do not appear to be biased by potential co-segregation of adiposity and AMY1 CN with ancestry.

Interestingly, while no difference in the association between AMY1 and adiposity was observed between subgroups of subjects characterized by varying degrees of Persian ancestry, the higher the Arab ancestry, the stronger the association with all adiposity traits (see “Methods” section, Supplementary Fig. 6). To explore what could drive this behavior, we evaluated the heritability of the three adiposity traits at varying degrees of ancestry (see “Methods” section). While, in general, the heritability of all adiposity traits was higher among Persians (42–44%) compared to Arabs (19–23%), Arabs (but not Persians) showed decreased heritability of these traits with increased ancestry (Supplementary Fig. 6). This was not driven by a decreased number or strength of pairwise kinship between subjects with strongest Arab ancestry, which might have deflated the heritability estimate. Instead we hypothesized that this could have been caused by ethnic-specific behavioral or environmental factors. We further assessed the association between PC1 and dietary behavior, finding a significant association between the degree of Arab ancestry and decreased tendency towards dietary restraint (P = 1.26 × 10−5; Supplementary Fig. 7), while dietary restraint behavior did not change between subgroups of subjects characterized by varying degrees of Persian ancestry (P > 0.05). Consistent with this finding, we observed a positive association between AMY1 CN and dietary restraint with increased Arab ancestry adjusting for age, sex and BMI, compared to Persians subjects (Supplementary Fig. 8).

Discussion

Elucidating the relationship between genetic architecture and obesity-related traits is of fundamental scientific and public-health concern, primarily due to the chronic comorbidities associated with obesity and the increased risk of premature mortality across various human populations22. The national STEPwise survey conducted in Qatar in 2012 reported an obesity epidemic (>70% of the adult population had a BMI ≥ 25 kg/m2), accompanied by an alarming rate of comorbidities in the affected population, such as hypertension (32.9% of respondents aged 18–64) and type II diabetes (17.6% of men and 15.9% of women)23.

While previous works have investigated the association of SNPs, epigenetic markers and obesity in the Gulf Arab world24,25,26,27, no studies to date have uncovered copy number variants influencing adiposity in this population.

Here, we discretely genotyped the range of copy number variation at AMY1 and AMY2A genes through coverage analysis of 30× whole genome sequencing data in 2935 individuals from Qatar, and showed that (1) copy number at both genes has similar distribution and correlation to previous reports1,3,6,16, and (2) AMY1 CN is negatively associated with trunk fat percentage.

Putative mechanisms by which AMY1 may be linked to obesity involves its role in modulating starch intake, sweet-taste perception, and carbohydrate digestion28,29 and gut microbiome composition30,31. It has been reported that subjects expressing lower AMY1 levels show higher blood glucose and delayed insulin response following starch ingestion28, suggesting that carriers of lower AMY1 CN may be at higher risk of developing insulin resistance if chronically relaying on starch-rich diets. In addition, increased ketonuria is associated with low serum amylase32 which further supports the hypothesis that individuals with lower AMY1 CN may not be fully adapted to a carbohydrate-based diet. Indeed, a combined mass-spec and NMR metabolomics study of homogeneous and age-matched normal weight French adult females highlighted increased reliance on lipid vs glucose metabolism for energy production in low CN carriers at AMY133.

Studies exploring how the human gut microbiome responds to AMY1 CN variation yielded conflicting results. For instance, it has been shown that gut microbiome of individuals carrying high AMY1 copies is enriched in microbes involved in complex polysaccharide degradation belonging to the Prevotella genus30, and that high Prevotella/Bacteroides ratio favors weight loss in response to dietary interventions34,35. Conversely, Poole and colleagues reported adiposity gain in germ-free mice following fecal microbiota transplantation from carriers of high AMY1 CN31.

Whereas the hypothesis that high AMY1 CN promotes obesity by modulating starch metabolism has still to be fully proven, it is known that AMY1 CN has followed different evolutionary trajectories between populations, as a function of the variability in starch content across traditional diets5. Given the ethnic heterogeneity of Qataris from QBB20,21, we sought to dissect possible ancestry-specific contributions to AMY1 CN association with adiposity in Qatar. Interestingly, we found that Arabs from Qatar (and females in particular) have, on average, unhealthier adiposity profiles, and significantly lower AMY1 and AMY2A CNs (PAMY1 = 1.32 × 10−10 and PAMY2A = 7.49 × 10−21, respectively) compared to Qataris of Persian ancestry. Higher AMY1 and AMY2A CN in Persians compared to Arabs from Qatar are consistent with differences in ancestral diets across the two ethnic groups. Indeed, whereas the traditional diet of populations with a history of nomadic pastoralism (e.g., Bedouin Arabs) relies extensively on proteinaceous resources and simple saccharides, starchy food resources traditionally comprise a substantial portion of the diet in traditional agricultural societies, such as Persians5. Higher ancestral AMY1 and AMY2A CN in Persians from Qatar compared to Arab may have resulted in increased resilience, as supported by their more favorable adiposity profile, to dietary changes introduced by the rapid growth and occidentalization of Qatar brought about by newfound oil-wealth, which paralleled the increase of obesity prevalence36.

Despite showing similar negative trends, the association between AMY1 CNs and measures of adiposity reached statistical significance only in Arabs, possibly due to lack of statistical power when testing Persians, given the smaller sample size or, indeed, population-specific effects.

We leveraged responses from the QBB on self-reported dietary restraint and observed a significant difference between Arabs and Persians in their tendency towards dietary restraint following weight gain (P = 4.29 × 10−5), with 60% of overweight or obese Persians restraining their diet compared to 54% of their Arab counterpart. In addition, we showed that increased Arab ancestry is associated with both decreased tendency towards dietary restraint following weight gain and increased association strength between AMY1 CN and dietary behavior, thus providing further evidence of the complexity of the association between AMY1 and adiposity, as it can be affected by population-specific environmental factors. This is supported by previous studies reporting a significant effect of the interaction between AMY1 CN and dietary starch intake on BMI37, and an association between AMY1 and BMI in overweight individuals on dietary intervention14. Unfortunately, food frequency questionnaires were not available to us for this cohort, and therefore we could not assess the contribution of dietary starch intake to the association between AMY1 CN and obesity in the Qatari population. Additional data on dietary variables is needed in order to dissect the specific environmental contributions underlying these observations.

Taken together, these findings could partially explain the fluctuating success rate of studies attempting to replicate the associations between AMY1 CN and obesity in adults, as compared to more consistent results observed in pediatric cohorts, where lifestyle choices and age-dependent gene-environment interactions should be less pronounced.

In conclusion, here we investigate the association between adiposity traits and discrete copy number variation from WGS at highly polymorphic loci in the Qatari population. We demonstrated that within this single national population of the Middle East, the strength of genetic associations may differ significantly across individuals with different ethnic ancestries. To help explain this disparity, we also demonstrate the power of a large population biobank such as QBB, rich with genomic and phenotypic information, not only to drive discoveries of novel associations in a part of the world that is relatively understudied in the literature, but to provide plausible explanations for such discrepancies.

Methods

Cohort description

The Qatar Biobank (QBB) is a national population-based medical health initiative started in 2012 with the aim of collecting samples and information on health and lifestyle from 60,000 Qatari adult nationals and long-term residents15. All subjects are enrolled in the Qatar Biobank via informed consent, and their genetic and phenotypic data made available for use in research studies. Anthropometrics details used in the current study, including BMI and body composition, were measured using the Seca stadiometer and Seca Bio Impedance Analysis (Seca GmbH and Co. KG, Hamburg, German) at Qatar Biobank facility at Hamad Medical City. Outliers (measurements greater than 3 standard deviations the dataset mean) were removed, and the data inverse-normal transformed.

The Qatar Biobank study was approved by the Qatar Biobank Institutional Review Board (IRB) Committee (IRB protocol E/2017/RES-ACC-0032/0002).

Whole-genome sequencing data

Subjects from the QBB were sequenced as part of the QGP. Whole-genome sequencing was performed on 2935 blood samples using Illumina HiSeq platform (150-bp paired-end) to an average coverage of 30×. Sequence reads were aligned to the Human Reference genome version GRCh37 using bwakit (v. 0.7.11).

Amylase gene copy number estimation

AMY1 and AMY2 CNs were estimated through sequencing coverage analysis by comparing the number of reads mapping to AMY1 and AMY2 genes to a reference local GC-matched and copy invariant region, as described in ref. 1. Read counts were extracted from WGS bam files using samtools38 (v. 1.6) with the command samtools view –c, defining the regions intervals with a corresponding bed file (coordinates based on GRCh37 genome assembly).

AMY1 corresponding region spans over 20 kb and includes the AMY1 gene plus two surrounding near-identical DNA sequences (chr1:104190000–104210000, 104227213–104247214 and 104284138–104304150, respectively). Local 20 kb reference region intervals were: chr1:104059996–104070000 and chr1:104460001–104469995. No quality threshold was applied for filtering reads mapping to this region, being the repetitive region responsible for low local mapping quality scores, as suggested in1.

AMY2A CN was estimated counting reads mapping to the interval chr1:104153700–104161939, which includes exons 1–3 of AMY2A, and to its local copy-invariant comparator interval (chr1:104045000–104085000). A minimum mapping quality threshold of 20 was applied (samtools option: -q 20).

AMY2B CN was estimated counting reads mapping to the interval chr1:104114335–104135000 and to its local copy-invariant comparator interval (chr1:104000000–104100000 and chr1:104304000–104500000). A minimum mapping quality threshold of 20 was applied (samtools option: -q 20).

Local read density was calculated for AMY1, AMY2A, AMY2B, and their reference regions, dividing the absolute read count by the region size (e.g., the total number of reads mapping to AMY1 region divided by 40k). Read densities were then normalized by their reference region read densities to obtain an estimate of their copy number state. Finally, raw CN estimates were assigned to integers by conditional rounding. More in detail, AMY2A and AMY2B read densities were first rounded to the nearest integer. AMY1 read densities were then rounded to the nearest even number if AMY2A CN was even, and to the nearest odd number if AMY2A CN was odd.

Polychoric correlation between CNs was estimated using polycor R package (v. 0.7–10; polychor function).

Evaluation of reads alignability at the amylase locus

We assessed the rate of misalignment of sequences mapping to the AMY1 and AMY2 genes by evaluating the fraction of properly paired reads (i.e., read pairs mapping with correct orientation with respect to one another, and with expected insert size) mapping to either AMY1 or AMY2A having unique alignment. Alignability was estimated on the same genomic regions used for CN calling at AMY1 and AMY2A. Within individual BAM files, uniquely mapping reads were defined based on the absence of the ‘XA:Z:’ and ‘SA:Z:’ tags (flagging secondary alignments and split reads, respectively) and the “*” score (flagging unmapped reads) in the mapping quality (MAPQ) field generated by bwa-mem (bwakit v. 0.7.11). Further, we evaluated the distribution of the mapping quality of reads aligned to the AMY1 and AMY2A genes.

Validation of copy number estimates

We used Droplet DigitalTM PCR39 (ddPCR, Bio-Rad) to experimentally validate CN estimates at the AMY1 and AMY2 loci, following a previously published protocol3. PCR primers and fluorescent probes used in this study are reported in Supplementary Table 3. All probes targeting the AMY1 (two independent probes) and AMY2A (one probe) genes were labeled with FAM, whereas control probes with HEX. We digested the DNA with NHeI restriction enzymes prior to amplification. The PCR reaction mix contained 0.25 ng/ul of DNA, 900 nM of each primer (target and control), and 250 nM of fluorescent probes. Droplet generation (20,000) was done by QX200 Automated Droplet Generator, and the droplets were read by QX200 Droplet Reader. Droplet counts were analyzed using QuantaSoft software, and the copy number was estimated by dividing the number of FAM-positive droplets by the number of HEX-positive droplets (Supplementary Fig. 9). For each individual, the reported copy number represents an average of three independent replicates. Given that AMY1 and AMY2A share odd/even parity, we checked the correctness of the AMY1 CN call using the AMY2A call, as done in ref. 3. For a given sample, if both AMY1 calls obtained from two independent probes were concordant, they were averaged. If only one was concordant, only the concordant AMY1 genotype was used. If both calls were discordant, they were averaged.

A further Independent in silico validation of AMY1 CN in the Qatari population was performed using AMYCNE18 (release: 2020-03-18) which was developed particularly for genes harboring more than four copies, and its accuracy in estimating AMY1 CN was assessed by the authors using ddPCR, making it particularly suitable for identifying AMY1 CN variations. Copy number at AMY1 was estimated using region files provided by AMYCNE and BAM coverage files obtained using TIDDIT40.

Loss-of-function and missense variants at the AMY1 gene

Coding-region variants at the AMY1 gene were annotated using SNPeff41 which implements coding effect prediction of genetic variants. Stop gained, frameshift, missense variants or inframe deletions were considered as high-impact variants.

AMY1, AMY2A, and adiposity traits association testing in the Qatari population

We tested the association between amylase genes CNs and adiposity traits in 2935 individuals from the QBB. Association testing was carried out using PopPAnTe19 (v. 1.0.2) which uses a variance component framework to model the resemblance among related individuals. Subjects showing zero CN at AMY1 were discarded from the analysis, and rare AMY1 CNs larger than 14 copies were set to 14. Sex, age at the sample collection, and the first 10 PCs from genome-wide data were included as covariates. The phenotypic covariance matrix between subjects was modeled using the matrix of the kinship between each pair of individuals, as evaluated by PLINK42. Indeed, the Qatari population is an isolated inbred population characterized by a large number of consanguineous families43. Pairs of individuals having a kinship lower than 0.05 were considered as unrelated (i.e., their kinship was considered to be zero).

We derived the Bonferroni-adjusted threshold for statistical significance by dividing a conventional alpha value of 0.05 by the number of tests performed, considering both the number of outcome variables (N = 3) and the number of predictors tested (i.e., AMY1 and AMY2A; N = 2).

AMY1 and adiposity traits association testing in Arabs and Persians from Qatar

To identify the ethnicity of each of the 2935 participants from the QBB, we leveraged genotypes at 48 ancestry-informative single-nucleotide polymorphisms (SNPs) from the WGS data to differentiate the three major Qatari subpopulations (Bedouin Arabs, Persians, East Africans) as described in refs. 20,21. Individuals whose majority ancestry did not belong to these three major ethnicities were considered admixed.

Subsequently, we sought for AMY1 association with adiposity traits using PopPAnTe (v. 1.0.2), in 948 Persians and 1518 Arabs from the QBB. Subjects showing zero CN at AMY1 were discarded from the analysis, and rare AMY1 CNs larger than 14 copies were set to 14. Sex, age at the sample collection, and the first 10 PCs from genome-wide data were included as covariates.

The Bonferroni-adjusted threshold for statistical significance was obtained by dividing a conventional alpha value of 0.05 by the number of tests performed, considering both the number of outcome variables (N = 3) and of groups tested (N = 2).

Arabs and Persians clustering based on genotypes at the amylase region

To verify whether some degree of admixture at the amylase genomic region was not properly captured by the ethnicity-informative SNPs20,21 used to assign subjects to the different ethnic groups, we carried out PCA on 6,229 SNPs and indels located within a 5-MB window surrounding AMY1 (chr1:99,159,954–109,301,314; Supplementary Fig. 4). PCA was performed using PLINK (v. 1.9) on LD-pruned high-quality variants (MAF > 0.01, genotyping rate >0.9, HWE deviation P > 10−6). LD pruning was carried on with PLINK (option: --indep-pairwise) using the following parameters: window size of 50-kb, shift of 5 variants, and r2 threshold of 0.05. This analysis highlighted the presence of a small number of outliers (NArabs = 75, NPersians = 34, Supplementary Fig. 4). Therefore, to rule out the possibility that these individuals could possibly be skewing the association signal in our primary analysis, we removed them from our dataset, and re-assessed the association between AMY1 CN and adiposity traits using PopPAnTe (v. 1.0.2), and including sex, age, and the first 10 PCs from genome-wide data as covariates.

Case/control AMY1 association with obesity in Arabs from Qatar

Association of AMY1 CNs with obesity was assessed in Arabs from the QBB by logistic regression using R (lme4 package, v. 1.1–21). Individuals with BMI ≥ 30 kg/m2 were considered as obese, whereas subjects with BMI < 25 kg/m2 were treated as controls. Rare AMY1 CNs larger than 14 were set to 14. Sex, age at the sample collection and the first 10 PCs from genome-wide data were included as covariates in the analysis.

AMY1 association with dietary restraint

In order to explore whether ethnic-specific behavioral variations underlie inter-population variability in AMY1 association with adiposity, we sought association between AMY1 copy number and dietary restraint, collected through self-administered questionnaires as part of the QBB initiative.

Association of self-reported dietary restraint with AMY1 CNs was evaluated in overweight subjects (BMI ≥ 25 kg/m2) of Persians or Arabs ancestry from the QBB by logistic regression in R (lme4 package, v. 1.1–21), including age, sex, BMI, and ethnicity as covariates. Rare AMY1 copy numbers larger than 14 were set to 14.

Dissecting the confounding effect of ethnicity

To dissect the effect of ethnicity in our analyses, we evaluated the association between the first principal component (PC1) values and AMY1 CNs, as well as adiposity traits. We also investigated the association between AMY1 CNs and adiposity traits, as well as the tendency towards dietary restraint behaviors, in subsets of individuals of Arab or Persians ancestry, binned according to their PC1 values (Supplementary Fig. 10). More in detail, we generated 10 sliding windows, each including 750 Arab individuals (with an overlap of 85 individuals) along with the first principal component in Arabs. Similarly, three sliding windows, each including 750 Persian individuals (with 85 individuals of overlap) were generated along with the first principal component in Persian. Within each window, we tested the association between AMY1 CN and BMI, total and trunk fat mass percentages using linear regression (stats R package, v. 3.6). Outliers (measurements greater than three standard deviations the dataset mean) were removed, and the data inverse normal transformed. Age and sex were included as covariates. Association with dietary restraint was assessed using logistic regression (stats R package, v. 3.6), and adjusting for sex, age, and BMI.

Heritability of the adiposity traits was estimated using PopPAnTe (v. 1.0.2), accounting for age and sex.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.