The selection landscape and genetic legacy of ancient Eurasians.

The Holocene (beginning around 12,000 years ago) encompassed some of the most significant changes in human evolution, with far-reaching consequences for the dietary, physical and mental health of present-day populations. Using a dataset of more than 1,600 imputed ancient genomes1, we modelled the selection landscape during the transition from hunting and gathering, to farming and pastoralism across West Eurasia. We identify key selection signals related to metabolism, including that selection at the FADS cluster began earlier than previously reported and that selection near the LCT locus predates the emergence of the lactase persistence allele by thousands of years. We also find strong selection in the HLA region, possibly due to increased exposure to pathogens during the Bronze Age. Using ancient individuals to infer local ancestry tracts in over 400,000 samples from the UK Biobank, we identify widespread differences in the distribution of Mesolithic, Neolithic and Bronze Age ancestries across Eurasia. By calculating ancestry-specific polygenic risk scores, we show that height differences between Northern and Southern Europe are associated with differential Steppe ancestry, rather than selection, and that risk alleles for mood-related phenotypes are enriched for Neolithic farmer ancestry, whereas risk alleles for diabetes and Alzheimer's disease are enriched for Western hunter-gatherer ancestry. Our results indicate that ancient selection and migration were large contributors to the distribution of phenotypic diversity in present-day Europeans.

100 ancient genomes show repeated population turnovers in Neolithic Denmark.

Major migration events in Holocene Eurasia have been characterized genetically at broad regional scales1-4. However, insights into the population dynamics in the contact zones are hampered by a lack of ancient genomic data sampled at high spatiotemporal resolution5-7. Here, to address this, we analysed shotgun-sequenced genomes from 100 skeletons spanning 7,300 years of the Mesolithic period, Neolithic period and Early Bronze Age in Denmark and integrated these with proxies for diet (13C and 15N content), mobility (87Sr/86Sr ratio) and vegetation cover (pollen). We observe that Danish Mesolithic individuals of the Maglemose, Kongemose and Ertebølle cultures form a distinct genetic cluster related to other Western European hunter-gatherers. Despite shifts in material culture they displayed genetic homogeneity from around 10,500 to 5,900 calibrated years before present, when Neolithic farmers with Anatolian-derived ancestry arrived. Although the Neolithic transition was delayed by more than a millennium relative to Central Europe, it was very abrupt and resulted in a population turnover with limited genetic contribution from local hunter-gatherers. The succeeding Neolithic population, associated with the Funnel Beaker culture, persisted for only about 1,000 years before immigrants with eastern Steppe-derived ancestry arrived. This second and equally rapid population replacement gave rise to the Single Grave culture with an ancestry profile more similar to present-day Danes. In our multiproxy dataset, these major demographic events are manifested as parallel shifts in genotype, phenotype, diet and land use.

Population genomics of post-glacial western Eurasia.

Western Eurasia witnessed several large-scale human migrations during the Holocene1-5. Here, to investigate the cross-continental effects of these migrations, we shotgun-sequenced 317 genomes-mainly from the Mesolithic and Neolithic periods-from across northern and western Eurasia. These were imputed alongside published data to obtain diploid genotypes from more than 1,600 ancient humans. Our analyses revealed a 'great divide' genomic boundary extending from the Black Sea to the Baltic. Mesolithic hunter-gatherers were highly genetically differentiated east and west of this zone, and the effect of the neolithization was equally disparate. Large-scale ancestry shifts occurred in the west as farming was introduced, including near-total replacement of hunter-gatherers in many areas, whereas no substantial ancestry shifts happened east of the zone during the same period. Similarly, relatedness decreased in the west from the Neolithic transition onwards, whereas, east of the Urals, relatedness remained high until around 4,000 BP, consistent with the persistence of localized groups of hunter-gatherers. The boundary dissolved when Yamnaya-related ancestry spread across western Eurasia around 5,000 BP, resulting in a second major turnover that reached most parts of Europe within a 1,000-year span. The genetic origin and fate of the Yamnaya have remained elusive, but we show that hunter-gatherers from the Middle Don region contributed ancestry to them. Yamnaya groups later admixed with individuals associated with the Globular Amphora culture before expanding into Europe. Similar turnovers occurred in western Siberia, where we report new genomic data from a 'Neolithic steppe' cline spanning the Siberian forest steppe to Lake Baikal. These prehistoric migrations had profound and lasting effects on the genetic diversity of Eurasian populations.

The role of circulating galectin-1 in type 2 diabetes and chronic kidney disease: evidence from cross-sectional, longitudinal and Mendelian randomisation analyses.

AIMS/HYPOTHESIS: Galectin-1 modulates inflammation and angiogenesis, and cross-sectional studies indicate that galectin-1 may be a uniting factor between obesity, type 2 diabetes and kidney function. We examined whether circulating galectin-1 can predict incidence of chronic kidney disease (CKD) and type 2 diabetes in a middle-aged population, and if Mendelian randomisation (MR) can provide evidence for causal direction of effects. METHODS: Participants (n = 4022; 58.6% women) in the Malmö Diet and Cancer Study-Cardiovascular Cohort enrolled between 1991 and 1994 (mean age 57.6 years) were examined. eGFR was calculated at baseline and after a mean follow-up of 16.6 ± 1.5 years. Diabetes status was ascertained through registry linkage (mean follow-up of 18.4 ± 6.1 years). The associations of baseline galectin-1 with incident CKD and type 2 diabetes were assessed with Cox regression, adjusting for established risk factors. In addition, a genome-wide association study on galectin-1 was performed to identify genetic instruments for two-sample MR analyses utilising the genetic associations obtained from the Chronic Kidney Disease Genetics (CKDGen) Consortium (41,395 cases and 439,303 controls) and the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) consortium (74,124 cases and 824,006 controls). One genome-wide significant locus in the galectin-1 gene region was identified (sentinel SNP rs7285699; p = 2.4 × 10-11). The association between galectin-1 and eGFR was also examined in individuals with newly diagnosed diabetes from the All New Diabetics In Scania (ANDIS) cohort. RESULTS: Galectin-1 was strongly associated with lower eGFR at baseline (p = 2.3 × 10-89) but not with incident CKD. However, galectin-1 was associated with increased risk of type 2 diabetes (per SD increase, HR 1.12; 95% CI 1.02, 1.24). Two-sample MR analyses could not ascertain a causal effect of galectin-1 on CKD (OR 0.92; 95% CI 0.82, 1.02) or type 2 diabetes (OR 1.05; 95% CI 0.98, 1.14) in a general population. However, in individuals with type 2 diabetes from ANDIS who belonged to the severe insulin-resistant diabetes subgroup and were at high risk of diabetic nephropathy, genetically elevated galectin-1 was significantly associated with higher eGFR (p = 5.7 × 10-3). CONCLUSIONS/INTERPRETATION: Galectin-1 is strongly associated with lower kidney function in cross-sectional analyses, and two-sample MR analyses suggest a causal protective effect on kidney function among individuals with type 2 diabetes at high risk of diabetic nephropathy. Future studies are needed to explore the mechanisms by which galectin-1 affects kidney function and whether it could be a useful target among individuals with type 2 diabetes for renal improvement.

Overweight, obesity and the risk of LADA: results from a Swedish case-control study and the Norwegian HUNT Study.

AIMS/HYPOTHESIS: Excessive weight is a risk factor for type 2 diabetes, but its role in the promotion of autoimmune diabetes is not clear. We investigated the risk of latent autoimmune diabetes in adults (LADA) in relation to overweight/obesity in two large population-based studies. METHODS: Analyses were based on incident cases of LADA (n = 425) and type 2 diabetes (n = 1420), and 1704 randomly selected control participants from a Swedish case-control study and prospective data from the Norwegian HUNT Study including 147 people with LADA and 1,012,957 person-years of follow-up (1984-2008). We present adjusted ORs and HRs with 95% CI. RESULTS: In the Swedish data, obesity was associated with an increased risk of LADA (OR 2.93, 95% CI 2.17, 3.97), which was even stronger for type 2 diabetes (OR 18.88, 95% CI 14.29, 24.94). The association was stronger in LADA with low GAD antibody (GADA;

Aortic diameter at age 65 in men with newly diagnosed type 2 diabetes.

OBJECTIVES: Type 2 diabetes mellitus has been linked to a decreased risk for abdominal aortic aneurysm (aortic diameter ≥30 mm, AAA) development in men. The aim of this study was to evaluate if such an effect is detectable already around the time of diabetes diagnosis. DESIGN: We cross-sectionally compared aortic diameter at ultrasound screening for AAA in 691 men aged 65 years with incipient or newly diagnosed type 2 diabetes (group A) with 18,262 65-year old control men without diabetes (group B). RESULTS: Aortic diameter did not differ between groups (18.8[17.4-20.8] vs. 19.0[17.5-28.7] mm; p = 0.43). AAA prevalence was 2.5% in group A and 1.5% in group B (p = .010). In logistic regression taking group differences in body mass index (BMI), smoking, presence of atherosclerotic disease and hypertension into account, the difference in AAA prevalence was no longer significant (p = .15). Among men in group A, C-peptide (r = .093; p = .034), but not HbA1c (r = .060; p = .24) correlated with aortic diameter. CONCLUSION: Among 65 year old men aortic diameter and AAA prevalence do not differ between those with newly diagnosed type 2 diabetes and those without diabetes. Putative protective effects of type 2 diabetes mellitus against aortic dilatation and AAA development therefore probably occur later after diagnosis of diabetes.

Global genomic and transcriptomic analysis of human pancreatic islets reveals novel genes influencing glucose metabolism.

Genetic variation can modulate gene expression, and thereby phenotypic variation and susceptibility to complex diseases such as type 2 diabetes (T2D). Here we harnessed the potential of DNA and RNA sequencing in human pancreatic islets from 89 deceased donors to identify genes of potential importance in the pathogenesis of T2D. We present a catalog of genetic variants regulating gene expression (eQTL) and exon use (sQTL), including many long noncoding RNAs, which are enriched in known T2D-associated loci. Of 35 eQTL genes, whose expression differed between normoglycemic and hyperglycemic individuals, siRNA of tetraspanin 33 (TSPAN33), 5'-nucleotidase, ecto (NT5E), transmembrane emp24 protein transport domain containing 6 (TMED6), and p21 protein activated kinase 7 (PAK7) in INS1 cells resulted in reduced glucose-stimulated insulin secretion. In addition, we provide a genome-wide catalog of allelic expression imbalance, which is also enriched in known T2D-associated loci. Notably, allelic imbalance in paternally expressed gene 3 (PEG3) was associated with its promoter methylation and T2D status. Finally, RNA editing events were less common in islets than previously suggested in other tissues. Taken together, this study provides new insights into the complexity of gene regulation in human pancreatic islets and better understanding of how genetic variation can influence glucose metabolism.

Evaluation of shared genetic susceptibility loci between autoimmune diseases and schizophrenia based on genome-wide association studies.

BACKGROUND: Epidemiological studies have documented higher than expected comorbidity (or, in some cases, inverse comorbidity) between schizophrenia and several autoimmune disorders. It remains unknown whether this comorbidity reflects shared genetic susceptibility loci. AIMS: The present study aimed to investigate whether verified genome wide significant variants of autoimmune disorders confer risk of schizophrenia, which could suggest a common genetic basis. METHODS: Seven hundred and fourteen genome wide significant risk variants of 25 autoimmune disorders were extracted from the NHGRI GWAS catalogue and examined for association to schizophrenia in the Psychiatric Genomics Consortium schizophrenia GWAS samples (36,989 cases and 113,075 controls). RESULTS: Two independent loci at 4q24 and 6p21.32-33 originally identified from GWAS of autoimmune diseases were found genome wide associated with schizophrenia (1.7 × 10-8 ≥ p ≥ 4.0 × 10-21). While these observations confirm the existence of shared genetic susceptibility loci between schizophrenia and autoimmune diseases, the findings did not show a significant enrichment. CONCLUSION: The findings do not support a genetic overlap in common SNPs between autoimmune diseases and schizophrenia that in part could explain the observed comorbidity from epidemiological studies.

Identification of rare high-risk copy number variants affecting the dopamine transporter gene in mental disorders.

BACKGROUND: The dopamine transporter, also known as solute carrier 6A3 (SLC6A3), plays an important role in synaptic transmission by regulating the reuptake of dopamine in the synapses. In line with this, variations in the gene encoding this transporter have been linked to both schizophrenia and affective disorders. Recently, copy number variants (CNVs) in SLC6A3 have been identified in healthy subjects but so far, the implication of CNVs affecting this gene in psychiatric diseases has not been addressed. AIMS: In the present study, we aimed to investigate whether CNVs affecting SLC6A3 represent rare high-risk variants of psychiatric disorders. METHODS: We performed a systematic screening for CNVs affecting SLC6A3 in 761 healthy controls, 672 schizophrenia patients, and 194 patients with bipolar disorder in addition to 253 family members from six large pedigrees affected by mental disorders using single nucleotide polymorphism arrays and subsequent verification by real-time polymerase chain reaction. RESULTS: We identified two duplications and one deletion affecting SLC6A3 in the patients, while no such CNVs were identified in any of the controls. The identified CNVs were of different sizes and two affected several genes in addition to SLC6A3. CONCLUSION: Our findings suggest that rare high-risk CNVs affecting the gene encoding the dopamine transporter contribute to the pathogenesis of schizophrenia and affective disorders.

3D facial landmarks: Inter-operator variability of manual annotation.

BACKGROUND: Manual annotation of landmarks is a known source of variance, which exist in all fields of medical imaging, influencing the accuracy and interpretation of the results. However, the variability of human facial landmarks is only sparsely addressed in the current literature as opposed to e.g. the research fields of orthodontics and cephalometrics. We present a full facial 3D annotation procedure and a sparse set of manually annotated landmarks, in effort to reduce operator time and minimize the variance. METHOD: Facial scans from 36 voluntary unrelated blood donors from the Danish Blood Donor Study was randomly chosen. Six operators twice manually annotated 73 anatomical and pseudo-landmarks, using a three-step scheme producing a dense point correspondence map. We analyzed both the intra- and inter-operator variability, using mixed-model ANOVA. We then compared four sparse sets of landmarks in order to construct a dense correspondence map of the 3D scans with a minimum point variance. RESULTS: The anatomical landmarks of the eye were associated with the lowest variance, particularly the center of the pupils. Whereas points of the jaw and eyebrows have the highest variation. We see marginal variability in regards to intra-operator and portraits. Using a sparse set of landmarks (n=14), that capture the whole face, the dense point mean variance was reduced from 1.92 to 0.54 mm. CONCLUSION: The inter-operator variability was primarily associated with particular landmarks, where more leniently landmarks had the highest variability. The variables embedded in the portray and the reliability of a trained operator did only have marginal influence on the variability. Further, using 14 of the annotated landmarks we were able to reduced the variability and create a dense correspondences mesh to capture all facial features.

Randomized open-label trial of semaglutide and dapagliflozin in patients with type 2 diabetes of different pathophysiology.

The limited understanding of the heterogeneity in the treatment response to antidiabetic drugs contributes to metabolic deterioration and cardiovascular complications1,2, stressing the need for more personalized treatment1. Although recent attempts have been made to classify diabetes into subgroups, the utility of such stratification in predicting treatment response is unknown3. We enrolled participants with type 2 diabetes (n = 239, 74 women and 165 men) and features of severe insulin-deficient diabetes (SIDD) or severe insulin-resistant diabetes (SIRD). Participants were randomly assigned to treatment with the glucagon-like peptide 1 receptor agonist semaglutide or the sodium-glucose cotransporter 2 inhibitor dapagliflozin for 6 months (open label). The primary endpoint was the change in glycated haemoglobin (HbA1c). Semaglutide induced a larger reduction in HbA1c levels than dapagliflozin (mean difference, 8.2 mmol mol-1; 95% confidence interval, -10.0 to -6.3 mmol mol-1), with a pronounced effect in those with SIDD. No difference in adverse events was observed between participants with SIDD and those with SIRD. Analysis of secondary endpoints showed greater reductions in fasting and postprandial glucose concentrations in response to semaglutide in participants with SIDD than in those with SIRD and a more pronounced effect on postprandial glucose by dapagliflozin in participants with SIDD than in those with SIRD. However, no significant interaction was found between drug assignment and the SIDD or SIRD subgroup. In contrast, continuous measures of body mass index, blood pressure, insulin secretion and insulin resistance were useful in identifying those likely to have the largest improvements in glycaemic control and cardiovascular risk factors by adding semaglutide or dapagliflozin. Thus, systematic evaluation of continuous pathophysiological variables can guide the prediction of the treatment response to these drugs and provide more information than stratified subgroups ( NCT04451837 ).

Digital lifestyle treatment improves long-term metabolic control in type 2 diabetes with different effects in pathophysiological and genetic subgroups.

To address the unmet need for scalable solutions for lifestyle treatment, we developed a new digital method to promote behavioral change. Here we report that patients with type-2 diabetes in Sweden (n = 331) exposed to the intervention have significantly improved HbA1c during a median follow-up of 1038 days (4 mmol/mol compared with matched controls; P = 0.009). This is paralleled by reduced body weight, ameliorated insulin secretion, increased physical activity, and cognitive eating restraints. Participants with high BMI and insulin resistance have an even larger response, as have non-risk allele carriers for the FTO gene. The findings open a new avenue for scalable lifestyle management with sustained efficacy and highlight a previously unrecognized opportunity for digital precision treatment based on genetics and individual pathophysiology. ClinicalTrials.gov NCT04624321.

Accuracy of haplotype estimation and whole genome imputation affects complex trait analyses in complex biobanks.

Sample recruitment for research consortia, biobanks, and personal genomics companies span years, necessitating genotyping in batches, using different technologies. As marker content on genotyping arrays varies, integrating such datasets is non-trivial and its impact on haplotype estimation (phasing) and whole genome imputation, necessary steps for complex trait analysis, remains under-evaluated. Using the iPSYCH dataset, comprising 130,438 individuals, genotyped in two stages, on different arrays, we evaluated phasing and imputation performance across multiple phasing methods and data integration protocols. While phasing accuracy varied by choice of method and data integration protocol, imputation accuracy varied mostly between data integration protocols. We demonstrate an attenuation in imputation accuracy within samples of non-European origin, highlighting challenges to studying complex traits in diverse populations. Finally, imputation errors can bias association tests, reduce predictive utility of polygenic scores. Carefully optimized data integration strategies enhance accuracy and replicability of complex trait analyses in complex biobanks.

DanMAC5: a browser of aggregated sequence variants from 8,671 whole genome sequenced Danish individuals.

OBJECTIVES: Allele counts of sequence variants obtained by whole genome sequencing (WGS) often play a central role in interpreting the results of genetic and genomic research. However, such variant counts are not readily available for individuals in the Danish population. Here, we present a dataset with allele counts for sequence variants (single nucleotide variants (SNVs) and indels) identified from WGS of 8,671 (5,418 females) individuals from the Danish population. The data resource is based on WGS data from three independent research projects aimed at assessing genetic risk factors for cardiovascular, psychiatric, and headache disorders. To enable the sharing of information on sequence variation in Danish individuals, we created summarized statistics on allele counts from anonymized data and made them available through the European Genome-phenome Archive (EGA, https://identifiers.org/ega. DATASET: EGAD00001009756 ) and in a dedicated browser, DanMAC5 (available at www.danmac5.dk ). The summary level data and the DanMAC5 browser provide insight into the allelic spectrum of sequence variants segregating in the Danish population, which is important in variant interpretation. DATA DESCRIPTION: Three WGS datasets with an average coverage of 30x were processed independently using the same quality control pipeline. Subsequently, we summarized, filtered, and merged allele counts to create a high-quality summary level dataset of sequence variants.

Depression pathophysiology, risk prediction of recurrence and comorbid psychiatric disorders using genome-wide analyses.

Depression is a common psychiatric disorder and a leading cause of disability worldwide. Here we conducted a genome-wide association study meta-analysis of six datasets, including >1.3 million individuals (371,184 with depression) and identified 243 risk loci. Overall, 64 loci were new, including genes encoding glutamate and GABA receptors, which are targets for antidepressant drugs. Intersection with functional genomics data prioritized likely causal genes and revealed new enrichment of prenatal GABAergic neurons, astrocytes and oligodendrocyte lineages. We found depression to be highly polygenic, with ~11,700 variants explaining 90% of the single-nucleotide polymorphism heritability, estimating that >95% of risk variants for other psychiatric disorders (anxiety, schizophrenia, bipolar disorder and attention deficit hyperactivity disorder) were influencing depression risk when both concordant and discordant variants were considered, and nearly all depression risk variants influenced educational attainment. Additionally, depression genetic risk was associated with impaired complex cognition domains. We dissected the genetic and clinical heterogeneity, revealing distinct polygenic architectures across subgroups of depression and demonstrating significantly increased absolute risks for recurrence and psychiatric comorbidity among cases of depression with the highest polygenic burden, with considerable sex differences. The risks were up to 5- and 32-fold higher than cases with the lowest polygenic burden and the background population, respectively. These results deepen the understanding of the biology underlying depression, its disease progression and inform precision medicine approaches to treatment.

Association between a genetic variant in the serotonin transporter gene (SLC6A4) and suicidal behavior in patients with schizophrenia.

BACKGROUND: The serotonin (5-hydroxytryptamin; 5-HT) system has a central role in the circuitry of cognition and emotions. Multiple lines of evidence suggest that genetic variation in the serotonin transporter gene (SLC6A4; 5-HTT) is associated with schizophrenia and suicidal behavior. In this study, we wanted to elucidate whether SLC6A4 variations is involved in attempted suicide among patients with schizophrenia in a Scandinavian case-control sample. METHODS: Patients diagnosed with schizophrenia from three Scandinavian samples were assessed for presence or absence of suicide attempts, based on record reviews and interview data. Seven SLC6A4 single nucleotide polymorphisms (SNPs) were genotyped in 837 schizophrenia patients and 1,473 control individuals. Association analyses and statistical evaluations were performed with the program UNPHASED (version 3.0.9). RESULTS: We observed an allele association between the SNP rs16965628, located in intron one of SLC6A4, and attempted suicide (adjusted p-value 0.01), among patients with schizophrenia. No association was found to a diagnosis of schizophrenia, when patients were compared to healthy control individuals. CONCLUSION: The gene SLC6A4 appears to be involved in suicidal ideation among patients with schizophrenia. Independent replication is needed before more firm conclusions can be drawn.

Effect of Digital Lifestyle Management on Metabolic Control and Quality of Life in Patients with Well-Controlled Type 2 Diabetes.

INTRODUCTION: The lack of effective, scalable solutions for lifestyle treatment is a global clinical problem, causing severe morbidity and mortality. Digital tools could enable broad utility, but long-term metabolic outcomes and the influence on quality of life are unclear. METHODS: We developed a new method for lifestyle treatment that promotes self-reflection and iterative behavioural change, provided as a digital tool, and evaluated its effect on glycaemic control in patients with type 2 diabetes with HbA1c below 52 mmol/mol (n = 297). As a secondary analysis, its effect on quality of life (using SF-12) was examined in both participants with and without diabetes (total n = 1914). The tool was evaluated during a 12-week randomization period to assess the existence of effect, with a subsequent open-label follow-up to study long-term outcomes. RESULTS: Participants were randomized to wait or access the intervention tool. The mean difference in HbA1c was 2 mmol/mol (95% CI - 4 to 0; P = 0.02) after 12 weeks in participants with type 2 diabetes. The groups were then merged to enable all participants to use the tool. The mean HbA1c reduction from baseline in patients with type 2 diabetes using the tool was 2 mmol/mol compared with matched controls (95% CI - 3 to 0; P = 0.005). In users with HbA1c above 45 mmol/mol, the mean difference between the groups was 4 mmol/mol (95% CI - 7 to - 2). The improvements were sustained during the follow-up of 1 year on average. Users of the tool also had improved quality of life from baseline to 6 months, mainly observed in non-diabetic participants. CONCLUSION: The tool does not require in-person reinforcement or increased healthcare resources, and the marginal cost is fundamentally lower than pharmacological treatment and most existing lifestyle interventions. The results therefore open a new means for self-managed lifestyle treatment with long-term metabolic efficacy that can benefit large numbers of people. TRIAL REGISTRATION: ClinicalTrials.gov NCT04624321 and NCT05006508.

Effect of self-managed lifestyle treatment on glycemic control in patients with type 2 diabetes.

The lack of effective, scalable solutions for lifestyle treatment is a global clinical problem, causing severe morbidity and mortality. We developed a method for lifestyle treatment that promotes self-reflection and iterative behavioral change, provided as a digital tool, and evaluated its effect in 370 patients with type 2 diabetes (ClinicalTrials.gov identifier: NCT04691973). Users of the tool had reduced blood glucose, both compared with randomized and matched controls (involving 158 and 204 users, respectively), as well as improved systolic blood pressure, body weight and insulin resistance. The improvement was sustained during the entire follow-up (average 730 days). A pathophysiological subgroup of obese insulin-resistant individuals had a pronounced glycemic response, enabling identification of those who would benefit in particular from lifestyle treatment. Natural language processing showed that the metabolic improvement was coupled with the self-reflective element of the tool. The treatment is cost-saving because of improved risk factor control for cardiovascular complications. The findings open an avenue for self-managed lifestyle treatment with long-term metabolic efficacy that is cost-saving and can reach large numbers of people.

Genetic correlates of phenotypic heterogeneity in autism.

The substantial phenotypic heterogeneity in autism limits our understanding of its genetic etiology. To address this gap, here we investigated genetic differences between autistic individuals (nmax = 12,893) based on core and associated features of autism, co-occurring developmental disabilities and sex. We conducted a comprehensive factor analysis of core autism features in autistic individuals and identified six factors. Common genetic variants were associated with the core factors, but de novo variants were not. We found that higher autism polygenic scores (PGS) were associated with lower likelihood of co-occurring developmental disabilities in autistic individuals. Furthermore, in autistic individuals without co-occurring intellectual disability (ID), autism PGS are overinherited by autistic females compared to males. Finally, we observed higher SNP heritability for autistic males and for autistic individuals without ID. Deeper phenotypic characterization will be critical in determining how the complex underlying genetics shape cognition, behavior and co-occurring conditions in autism.