Clinical and genetic characteristics of congenital hyperinsulinism in Norway: A nationwide cohort study.

PURPOSE: Congenital hyperinsulinism (CHI) is a rare, monogenic disease characterized by excessive insulin secretion. We aimed to evaluate all probands with suspected CHI in Norway registered over the past two decades. METHODS: The study included 98 probands. Clinical data were cumulated from medical records. All probands were screened for variants in the genes ABCC8 and KCNJ11. Other CHI-related genes were Sanger-sequenced as indicated by the patients' phenotype (N=75) or analyzed by next-generation sequencing employing a panel of 30 CHI-related genes (N=23). RESULTS: Twenty-one probands (21%) received a diagnosis other than CHI, the most common being idiopathic ketotic hypoglycemia (9%) or syndromic hyperinsulinism (4%). In the final cohort of 77 CHI probands, genetic findings were revealed in 46 (60%). ABCC8 variants were most common (N=40) and five novel variants were identified. One proband harbored both the pathogenic GCK variant p.(Ala456Val) and the ABCC8 variant p.(Gly505Cys). Although most ABCC8 variants caused immediate disease onset with severe hypoglycemia and were diazoxide-unresponsive, eight probands had a heterozygous, apparently dominant variant with milder phenotype. Two probands had pathogenic variants in GLUD1, whereas variants in HADH, HNF4A, KCNJ11, and HK1 were identified in one proband each, the latter being non-coding. Neurologic sequelae were reported in 53% of the CHI probands. Of non-surgically treated probands, 43% had spontaneous resolution. The minimum birth prevalence of CHI in Norway is 1:19,400 live births. MAIN CONCLUSIONS: Individuals with disease-causing ABCC8 variants dominated our cohort. Patients with known genetic etiology had earlier and more severe disease-onset than genetically unsolved patients.

Molecular mechanism of HNF-1A-mediated HNF4A gene regulation and promoter-driven HNF4A-MODY diabetes.

Monogenic diabetes is a gateway to precision medicine through molecular mechanistic insight. Hepatocyte nuclear factor 1A (HNF-1A) and HNF-4A are transcription factors that engage in crossregulatory gene transcription networks to maintain glucose-stimulated insulin secretion in pancreatic ß cells. Variants in the HNF1A and HNF4A genes are associated with maturity-onset diabetes of the young (MODY). Here, we explored 4 variants in the P2-HNF4A promoter region: 3 in the HNF-1A binding site and 1 close to the site, which were identified in 63 individuals from 21 families of different MODY disease registries across Europe. Our goal was to study the disease causality for these variants and to investigate diabetes mechanisms on the molecular level. We solved a crystal structure of HNF-1A bound to the P2-HNF4A promoter and established a set of techniques to probe HNF-1A binding and transcriptional activity toward different promoter variants. We used isothermal titration calorimetry, biolayer interferometry, x-ray crystallography, and transactivation assays, which revealed changes in HNF-1A binding or transcriptional activities for all 4 P2-HNF4A variants. Our results suggest distinct disease mechanisms of the promoter variants, which can be correlated with clinical phenotype, such as age of diagnosis of diabetes, and be important tools for clinical utility in precision medicine.

Bioinformatics pipeline for the systematic mining genomic and proteomic variation linked to rare diseases: The example of monogenic diabetes.

Monogenic diabetes is characterized as a group of diseases caused by rare variants in single genes. Like for other rare diseases, multiple genes have been linked to monogenic diabetes with different measures of pathogenicity, but the information on the genes and variants is not unified among different resources, making it challenging to process them informatically. We have developed an automated pipeline for collecting and harmonizing data on genetic variants linked to monogenic diabetes. Furthermore, we have translated variant genetic sequences into protein sequences accounting for all protein isoforms and their variants. This allows researchers to consolidate information on variant genes and proteins linked to monogenic diabetes and facilitates their study using proteomics or structural biology. Our open and flexible implementation using Jupyter notebooks enables tailoring and modifying the pipeline and its application to other rare diseases.

Intrauterine Growth and Offspring Neurodevelopmental Traits: A Mendelian Randomization Analysis of the Norwegian Mother, Father and Child Cohort Study (MoBa).

Importance: Conventional epidemiological analyses have suggested that lower birth weight is associated with later neurodevelopmental difficulties; however, it is unclear whether this association is causal. Objective: To investigate the relationship between intrauterine growth and offspring neurodevelopmental difficulties. Design, Setting, and Participants: MoBa is a population-based pregnancy cohort that recruited pregnant women from June 1999 to December 2008 included approximately 114 500 children, 95 200 mothers, and 75 200 fathers. Observational associations between birth weight and neurodevelopmental difficulties were assessed with a conventional epidemiological approach. Mendelian randomization analyses were performed to investigate the potential causal association between maternal allele scores for birth weight and offspring neurodevelopmental difficulties conditional on offspring allele scores. Exposures: Birth weight and maternal allele scores for birth weight (derived from genetic variants robustly associated with birth weight) were the exposures in the observational and mendelian randomization analyses, respectively. Main Outcomes and Measures: Clinically relevant maternal ratings of offspring neurodevelopmental difficulties at 6 months, 18 months, 3 years, 5 years, and 8 years of age assessing language and motor difficulties, inattention and hyperactivity-impulsivity, social communication difficulties, and repetitive behaviors. Results: The conventional epidemiological sample included up to 46 970 offspring, whereas the mendelian randomization sample included up to 44 134 offspring (median offspring birth year, 2005 [range, 1999-2009]; mean [SD] maternal age at birth, 30.1 [4.5] years; mean [SD] paternal age at birth, 32.5 [5.1] years). The conventional epidemiological analyses found evidence that birth weight was negatively associated with several domains at multiple offspring ages (outcome of autism-related trait scores: Social Communication Questionnaire [SCQ]-full at 3 years, ß = -0.046 [95% CI, -0.057 to -0.034]; SCQ-Restricted and Repetitive Behaviors subscale at 3 years, ß = -0.049 [95% CI, -0.060 to -0.038]; attention-deficit/hyperactivity disorder [ADHD] trait scores: Child Behavior Checklist [CBCL]-ADHD subscale at 18 months, ß = -0.035 [95% CI, -0.045 to -0.024]; CBCL-ADHD at 3 years, ß = -0.032 [95% CI, -0.043 to -0.021]; CBCL-ADHD at 5 years, ß = -0.050 [95% CI, -0.064 to -0.037]; Rating Scale for Disruptive Behavior Disorders [RS-DBD]-ADHD at 8 years, ß = -0.036 [95% CI, -0.049 to -0.023]; RS-DBD-Inattention at 8 years, ß = -0.037 [95% CI, -0.050 to -0.024]; RS-DBD-Hyperactive-Impulsive Behavior at 8 years, ß = -0.027 [95% CI, -0.040 to -0.014]; Conners Parent Rating Scale-Revised [Short Form] at 5 years, ß = -0.041 [95% CI, -0.054 to -0.028]; motor scores: Ages and Stages Questionnaire-Motor Difficulty [ASQ-MOTOR] at 18 months, ß = -0.025 [95% CI, -0.035 to -0.015]; ASQ-MOTOR at 3 years, ß = -0.029 [95% CI, -0.040 to -0.018]; and Child Development Inventory-Gross and Fine Motor Skills at 5 years, ß = -0.028 [95% CI, -0.042 to -0.015]). Mendelian randomization analyses did not find any evidence for an association between maternal allele scores for birth weight and offspring neurodevelopmental difficulties. Conclusions and Relevance: This study found that the maternal intrauterine environment, as proxied by maternal birth weight genetic variants, is unlikely to be a major determinant of offspring neurodevelopmental outcomes.

Maternal Fiber Intake During Pregnancy and Development of Attention-Deficit/Hyperactivity Disorder Symptoms Across Childhood: The Norwegian Mother, Father, and Child Cohort Study.

BACKGROUND: Epidemiological studies suggest that maternal diet quality during pregnancy may influence the risk of neurodevelopmental disorders in offspring. Here, we investigated associations between maternal intake of dietary fiber and attention-deficit/hyperactivity disorder (ADHD) symptoms in early childhood. METHODS: We used longitudinal data of up to 21,852 mother-father-child trios (49.2% female offspring) from MoBa (the Norwegian Mother, Father, and Child Cohort Study). The relationships between maternal fiber intake during pregnancy and offspring ADHD symptoms at ages 3, 5, and 8 years were examined using 1) multivariate regression (overall levels of ADHD symptoms), 2) latent class analysis (subclasses of ADHD symptoms by sex at each age), and 3) latent growth curves (longitudinal change in offspring ADHD symptoms). Covariates were ADHD polygenic scores in child and parents, total energy intake and energy-adjusted sugar intake, parental ages at birth of the child, and sociodemographic factors. RESULTS: Higher maternal prenatal fiber intake was associated with lower offspring ADHD symptom scores at all ages (Bage3 = -0.14 [95% CI, -0.18 to -0.10]; Bage5 = -0.14 [95% CI, -0.19 to -0.09]; Bage8 = -0.14 [95% CI, -0.20 to -0.09]). Of the derived low/middle/high subclasses of ADHD symptoms, fiber was associated with lower risk of belonging to the middle subclass for boys and girls and to the high subclass for girls only (middle: odds ratioboys 0.91 [95% CI, 0.86 to 0.97]/odds ratiogirls 0.86 [95% CI, 0.81 to 0.91]; high: odds ratiogirls 0.82 [95% CI, 0.72 to 0.94]). Maternal fiber intake and rate of change in child ADHD symptoms across ages were not associated. CONCLUSIONS: Low prenatal maternal fiber intake may increase symptom levels of ADHD in offspring during childhood, independently of genetic predisposition to ADHD, unhealthy dietary exposures, and sociodemographic factors.

Congenital hyperinsulinism. / Medfødt hyperinsulinisme.

This clinical review will give doctors who work with children and neonates an introduction to the diagnosis and treatment of congenital hyperinsulinism, the most common cause of persistent neonatal hypoglycaemia. The condition is a rare monogenic disorder characterised by elevated insulin secretion and is a result of mutations in genes that regulate insulin secretion from pancreatic beta cells. The anabolic effect of insulin induces systemic glucose uptake and inhibits gluconeogenesis, glycogenolysis, ketogenesis and lipolysis. Low levels of glucose and ketone bodies in the blood are harmful to the central nervous system and can lead to brain damage or death. Early diagnosis and treatment of congenital hyperinsulinism are therefore crucial for a good prognosis.

Structural properties of the HNF-1A transactivation domain.

Hepatocyte nuclear factor 1α (HNF-1A) is a transcription factor with important gene regulatory roles in pancreatic ß-cells. HNF1A gene variants are associated with a monogenic form of diabetes (HNF1A-MODY) or an increased risk for type 2 diabetes. While several pancreatic target genes of HNF-1A have been described, a lack of knowledge regarding the structure-function relationships in HNF-1A prohibits a detailed understanding of HNF-1A-mediated gene transcription, which is important for precision medicine and improved patient care. Therefore, we aimed to characterize the understudied transactivation domain (TAD) of HNF-1A in vitro. We present a bioinformatic approach to dissect the TAD sequence, analyzing protein structure, sequence composition, sequence conservation, and the existence of protein interaction motifs. Moreover, we developed the first protocol for the recombinant expression and purification of the HNF-1A TAD. Small-angle X-ray scattering and synchrotron radiation circular dichroism suggested a disordered conformation for the TAD. Furthermore, we present functional data on HNF-1A undergoing liquid-liquid phase separation, which is in line with in silico predictions and may be of biological relevance for gene transcriptional processes in pancreatic ß-cells.

Extending protein interaction networks using proteoforms and small molecules.

MOTIVATION: Biological network analysis for high-throughput biomedical data interpretation relies heavily on topological characteristics. Networks are commonly composed of nodes representing genes or proteins that are connected by edges when interacting. In this study, we use the rich information available in the Reactome pathway database to build biological networks accounting for small molecules and proteoforms modeled using protein isoforms and post-translational modifications to study the topological changes induced by this refinement of the network representation. RESULTS: We find that improving the interactome modeling increases the number of nodes and interactions, but that isoform and post-translational modification annotation is still limited compared to what can be expected biologically. We also note that small molecule information can distort the topology of the network due to the high connectedness of these molecules, which does not necessarily represent the reality of biology. However, by restricting the connections of small molecules to the context of biochemical reactions, we find that these improve the overall connectedness of the network and reduce the prevalence of isolated components and nodes. Overall, changing the representation of the network alters the prevalence of articulation points and bridges globally but also within and across pathways. Hence, some molecules can gain or lose in biological importance depending on the level of detail of the representation of the biological system, which might in turn impact network-based studies of diseases or druggability. AVAILABILITY AND IMPLEMENTATION: Networks are constructed based on data publicly available in the Reactome Pathway knowledgebase: reactome.org.

The Composite Autonomic Symptom Score 31 Questionnaire: A Sensitive Test to Detect Risk for Autonomic Neuropathy.

Background and Aims: Autonomic neuropathy is a common but often neglected complication of diabetes, prediabetes, and even in individuals with an elevated risk of diabetes. The Composite Autonomic Symptom Score (COMPASS) 31 is a validated and easy-to-use questionnaire regarding autonomic symptoms. We aimed to use a digitally, Norwegian version of the COMPASS 31 in people with different durations of diabetes and healthy controls to consider feasibility and to investigate if scores could discriminate between positive and negative outcomes for established tests for diabetic neuropathy, including cardiovascular autonomic neuropathy (CAN) and a novel method of examining the gastrointestinal visceral sensitivity. Method: We included 21 participants with longstanding type 2 diabetes, 15 with early type 2 diabetes, and 30 matched controls. The mean age for all groups was 69 years. Participants were phenotyped by cardiovascular autonomic reflex tests, electrical skin conductance, sural nerve electrophysiology, and the monofilament test. As a proxy for gastrointestinal visceral and autonomic nerve function, evoked potentials were measured following rapid rectal balloon distention. Results: Participants with longstanding diabetes scored a median (IQR) of 14.9 (10.8-28.7) points, early diabetes of 7.3 (1.6-15.2), and matched controls of 8.6 (4.1-21.6), p = 0.04. Women and men scored 14.4 (5.5-28.7) and 7.8 (3.6-14.6) points, respectively, p = 0.01. Participants with definite or borderline CAN scored 14.3 (10.4-31.9) points, compared to participants with no CAN, 8.3 (3.2-21.5), p = 0.04. Lowering the diagnostic cut-off from 16 to 10 points increased the sensitivity from 0.33 to 0.83, with a decreased specificity from 0.68 to 0.55. Conclusion: We successfully used COMPASS 31 in Norwegian. Thus, following the guidelines, we suggest clinical implementation for the assessment of autonomic neuropathy. Participants with longstanding diabetes had an increased likelihood of symptoms and signs of autonomic neuropathy. For screening purposes, the sensitivity was improved by lowering the cut-off to 10 points, with a lower score nearly excluding the diagnosis.

Developmental milestones in early childhood and genetic liability to neurodevelopmental disorders.

BACKGROUND: Timing of developmental milestones, such as age at first walking, is associated with later diagnoses of neurodevelopmental disorders. However, its relationship to genetic risk for neurodevelopmental disorders in the general population is unknown. Here, we investigate associations between attainment of early-life language and motor development milestones and genetic liability to autism, attention deficit hyperactivity disorder (ADHD), and schizophrenia. METHODS: We use data from a genotyped sub-set (N = 25699) of children in the Norwegian Mother, Father and Child Cohort Study (MoBa). We calculate polygenic scores (PGS) for autism, ADHD, and schizophrenia and predict maternal reports of children's age at first walking, first words, and first sentences, motor delays (18 months), and language delays and a generalised measure of concerns about development (3 years). We use linear and probit regression models in a multi-group framework to test for sex differences. RESULTS: We found that ADHD PGS were associated with earlier walking age (ß = -0.033, padj < 0.001) in both males and females. Additionally, autism PGS were associated with later walking (ß = 0.039, padj = 0.006) in females only. No robust associations were observed for schizophrenia PGS or between any neurodevelopmental PGS and measures of language developmental milestone attainment. CONCLUSIONS: Genetic liabilities for neurodevelopmental disorders show some specific associations with the age at which children first walk unsupported. Associations are small but robust and, in the case of autism PGS, differentiated by sex. These findings suggest that early-life motor developmental milestone attainment is associated with genetic liability to ADHD and autism in the general population.

A novel splice-affecting HNF1A variant with large population impact on diabetes in Greenland.

Background: The genetic disease architecture of Inuit includes a large number of common high-impact variants. Identification of such variants contributes to our understanding of the genetic aetiology of diseases and improves global equity in genomic personalised medicine. We aimed to identify and characterise novel variants in genes associated with Maturity Onset Diabetes of the Young (MODY) in the Greenlandic population. Methods: Using combined data from Greenlandic population cohorts of 4497 individuals, including 448 whole genome sequenced individuals, we screened 14 known MODY genes for previously identified and novel variants. We functionally characterised an identified novel variant and assessed its association with diabetes prevalence and cardiometabolic traits and population impact. Findings: We identified a novel variant in the known MODY gene HNF1A with an allele frequency of 1.9% in the Greenlandic Inuit and absent elsewhere. Functional assays indicate that it prevents normal splicing of the gene. The variant caused lower 30-min insulin (ß = -232 pmol/L, ßSD = -0.695, P = 4.43 × 10-4) and higher 30-min glucose (ß = 1.20 mmol/L, ßSD = 0.441, P = 0.0271) during an oral glucose tolerance test. Furthermore, the variant was associated with type 2 diabetes (OR 4.35, P = 7.24 × 10-6) and HbA1c (ß = 0.113 HbA1c%, ßSD = 0.205, P = 7.84 × 10-3). The variant explained 2.5% of diabetes variance in Greenland. Interpretation: The reported variant has the largest population impact of any previously reported variant within a MODY gene. Together with the recessive TBC1D4 variant, we show that close to 1 in 5 cases of diabetes (18%) in Greenland are associated with high-impact genetic variants compared to 1-3% in large populations. Funding: Novo Nordisk Foundation, Independent Research Fund Denmark, and Karen Elise Jensen's Foundation.

Subtype-Specific Surface Proteins on Adipose Tissue Macrophages and Their Association to Obesity-Induced Insulin Resistance.

A chronic low-grade inflammation, originating in the adipose tissue, is considered a driver of obesity-associated insulin resistance. Macrophage composition in white adipose tissue is believed to contribute to the pathogenesis of metabolic diseases, but a detailed characterization of pro- and anti-inflammatory adipose tissue macrophages (ATMs) in human obesity and how they are distributed in visceral- and subcutaneous adipose depots is lacking. In this study, we performed a surface proteome screening of pro- and anti-inflammatory ATMs in both subcutaneous- (SAT) and visceral adipose tissue (VAT) and evaluated their relationship with systemic insulin resistance. From the proteomics screen we found novel surface proteins specific to M1-like- and M2-like macrophages, and we identified depot-specific immunophenotypes in SAT and VAT. Furthermore, we found that insulin resistance, assessed by HOMA-IR, was positively associated with a relative increase in pro-inflammatory M1-like macrophages in both SAT and VAT.

Structural and biophysical characterization of transcription factor HNF-1A as a tool to study MODY3 diabetes variants.

Hepatocyte nuclear factor 1A (HNF-1A) is a transcription factor expressed in several embryonic and adult tissues, modulating the expression of numerous target genes. Pathogenic variants in the HNF1A gene are known to cause maturity-onset diabetes of the young 3 (MODY3 or HNF1A MODY), a disease characterized by dominant inheritance, age of onset before 25 to 35 years of age, and pancreatic ß-cell dysfunction. A precise diagnosis can alter management of this disease, as insulin can be exchanged with sulfonylurea tablets and genetic counseling differs from polygenic forms of diabetes. Therefore, more knowledge on the mechanisms of HNF-1A function and the level of pathogenicity of the numerous HNF1A variants is required for precise diagnostics. Here, we structurally and biophysically characterized an HNF-1A protein containing both the DNA-binding domain and the dimerization domain, and determined the folding and DNA-binding capacity of two established MODY3 HNF-1A variant proteins (P112L, R263C) and one variant of unknown significance (N266S). All three variants showed reduced functionality compared to the WT protein. Furthermore, while the R263C and N266S variants displayed reduced binding to an HNF-1A target promoter, we found the P112L variant was unstable in vitro and in cells. Our results support and mechanistically explain disease causality for these investigated variants and present a novel approach for the dissection of structurally unstable and DNA-binding defective variants. This study indicates that structural and biochemical investigation of HNF-1A is a valuable tool in reliable variant classification needed for precision diabetes diagnostics and management.

Early manifestations of genetic risk for neurodevelopmental disorders.

BACKGROUND: Attention deficit/hyperactivity disorder (ADHD), autism spectrum disorder (autism) and schizophrenia are highly heritable neurodevelopmental disorders, affecting the lives of many individuals. It is important to increase our understanding of how the polygenic risk for neurodevelopmental disorders manifests during childhood in boys and girls. METHODS: Polygenic risk scores (PRS) for ADHD, autism and schizophrenia were calculated in a subsample of 15 205 children from the Norwegian Mother, Father and Child Cohort Study (MoBa). Mother-reported traits of repetitive behavior, social communication, language and motor difficulties, hyperactivity and inattention were measured in children at 6 and 18 months, 3, 5 and 8 years. Linear regression models in a multigroup framework were used to investigate associations between the three PRS and dimensional trait measures in MoBa, using sex as a grouping variable. RESULTS: Before the age of 2, the ADHD PRS was robustly associated with hyperactivity and inattention, with increasing strength up to 8 years, and with language difficulties at age 5 and 8. The autism PRS was robustly associated with language difficulties at 18 months, motor difficulties at 36 months, and hyperactivity and inattention at 8 years. We did not identify robust associations for the schizophrenia PRS. In general, the PRS associations were similar in boys and girls. The association between ADHD PRS and hyperactivity at 18 months was, however, stronger in boys. CONCLUSIONS: Polygenic risk for autism and ADHD in the general population manifests early in childhood and broadly across behavioral measures of neurodevelopmental traits.

Maternal and offspring genetic risk score analyses of fetal alcohol exposure and attention-deficit hyperactivity disorder risk in offspring.

BACKGROUND: Studies investigating the effects of prenatal alcohol exposure on childhood attention-deficit hyperactivity disorder (ADHD) symptoms using conventional observational designs have reported inconsistent findings, which may be affected by unmeasured confounding and maternal and fetal ability to metabolize alcohol. We used genetic variants from the alcohol metabolizing genes, alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH), as proxies for fetal alcohol exposure to investigate their association with risk of offspring ADHD symptoms around age 7-8 years. METHODS: We used data from 3 longitudinal pregnancy cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC), Generation R study (GenR), and the Norwegian Mother, Father and Child Cohort study (MoBa). Genetic risk scores (GRS) for alcohol use and metabolism using 36 single nucleotide polymorphisms (SNPs) from ADH and ALDH genes were calculated for mothers (NALSPAC  = 8196; NMOBA  = 13,614), fathers (NMOBA  = 13,935), and offspring (NALSPAC =8,237; NMOBA =14,112; NGENR =2,661). Associations between maternal GRS and offspring risk of ADHD symptoms were tested in the full sample to avoid collider bias. Offspring GRS analyses were stratified by maternal drinking status. RESULTS: The pooled estimate in maternal GRS analyses adjusted for offspring GRS in ALSPAC and MoBa was OR = 0.99, 95%CI 0.97-1.02. The pooled estimate in offspring GRS analyses stratified by maternal drinking status across all the cohorts was as follows: ORDRINKING  = 0.98, 95% CI 0.94-1.02; ORNO DRINKING  = 0.99, 95% CI 0.97-1.02. These findings remained similar after accounting for maternal genotype data in ALSPAC and maternal and paternal genotype data in MoBa. CONCLUSIONS: We did not find evidence for a causal effect of fetal alcohol exposure on risk of ADHD symptoms in offspring. The results may be affected by limited power to detect small effects and outcome assessment.

Genetic Liability for Schizophrenia and Childhood Psychopathology in the General Population.

Genetic liability for schizophrenia is associated with psychopathology in early life. It is not clear if these associations are time dependent during childhood, nor if they are specific across different forms of psychopathology. Using genotype and questionnaire data on children (N = 15 105) from the Norwegian Mother, Father and Child Cohort Study, we used schizophrenia polygenic risk scores to test developmental stability in associations with measures of emotional and behavioral problems between 18 months and 5 years, and domain specificity in associations with symptoms of depression, anxiety, conduct problems, oppositionality, inattention, and hyperactivity at 8 years. We then sought to identify symptom profiles-across development and domains-associated with schizophrenia polygenic liability. We found evidence for developmental stability in associations between schizophrenia polygenic risk scores and emotional and behavioral problems, with the latter being mediated specifically via the rate of change in symptoms (ß slope = 0.032; 95% CI: 0.007-0.057). At age 8, associations were better explained by a model of symptom-specific polygenic effects rather than effects mediated via a general psychopathology factor or by domain-specific factors. Overall, individuals with higher schizophrenia polygenic risk scores were more likely (OR = 1.310 [95% CIs: 1.122-1.528]) to have a profile of increasing behavioral and emotional symptoms in early childhood, followed by elevated symptoms of conduct disorder, oppositionality, hyperactivity, and inattention by age 8. Schizophrenia-associated alleles are linked to specific patterns of early-life psychopathology. The associations are small, but findings of this nature can help us better understand the developmental emergence of schizophrenia.

Population prevalence and inheritance pattern of recurrent CNVs associated with neurodevelopmental disorders in 12,252 newborns and their parents.

Recurrent copy number variations (CNVs) are common causes of neurodevelopmental disorders (NDDs) and associated with a range of psychiatric traits. These CNVs occur at defined genomic regions that are particularly prone to recurrent deletions and duplications and often exhibit variable expressivity and incomplete penetrance. Robust estimates of the population prevalence and inheritance pattern of recurrent CNVs associated with neurodevelopmental disorders (NDD CNVs) are lacking. Here we perform array-based CNV calling in 12,252 mother-father-child trios from the Norwegian Mother, Father, and Child Cohort Study (MoBa) and analyse the inheritance pattern of 26 recurrent NDD CNVs in 13 genomic regions. We estimate the total prevalence of recurrent NDD CNVs (duplications and deletions) in live-born children to 0.48% (95% C.I.: 0.37-0.62%), i.e., ~1 in 200 newborns has either a deletion or duplication in these NDDs associated regions. Approximately a third of the newborn recurrent NDD CNVs (34%, N = 20/59) are de novo variants. We provide prevalence estimates and inheritance information for each of the 26 NDD CNVs and find higher prevalence than previously reported for 1q21.1 deletions (~1:2000), 15q11.2 duplications (~1:4000), 15q13.3 microdeletions (~1:2500), 16p11.2 proximal microdeletions (~1:2000) and 17q12 deletions (~1:4000) and lower than previously reported prevalence for the 22q11.2 deletion (~1:12,000). In conclusion, our analysis of an unselected and representative population of newborns and their parents provides a clearer picture of the rate of recurrent microdeletions/duplications implicated in neurodevelopmental delay. These results will provide an important resource for genetic diagnostics and counseling.

Unsupervised Clustering of Missense Variants in HNF1A Using Multidimensional Functional Data Aids Clinical Interpretation.

Exome sequencing in diabetes presents a diagnostic challenge because depending on frequency, functional impact, and genomic and environmental contexts, HNF1A variants can cause maturity-onset diabetes of the young (MODY), increase type 2 diabetes risk, or be benign. A correct diagnosis matters as it informs on treatment, progression, and family risk. We describe a multi-dimensional functional dataset of 73 HNF1A missense variants identified in exomes of 12,940 individuals. Our aim was to develop an analytical framework for stratifying variants along the HNF1A phenotypic continuum to facilitate diagnostic interpretation. HNF1A variant function was determined by four different molecular assays. Structure of the multi-dimensional dataset was explored using principal component analysis, k-means, and hierarchical clustering. Weights for tissue-specific isoform expression and functional domain were integrated. Functionally annotated variant subgroups were used to re-evaluate genetic diagnoses in national MODY diagnostic registries. HNF1A variants demonstrated a range of behaviors across the assays. The structure of the multi-parametric data was shaped primarily by transactivation. Using unsupervised learning methods, we obtained high-resolution functional clusters of the variants that separated known causal MODY variants from benign and type 2 diabetes risk variants and led to reclassification of 4% and 9% of HNF1A variants identified in the UK and Norway MODY diagnostic registries, respectively. Our proof-of-principle analyses facilitated informative stratification of HNF1A variants along the continuum, allowing improved evaluation of clinical significance, management, and precision medicine in diabetes clinics. Transcriptional activity appears a superior readout supporting pursuit of transactivation-centric experimental designs for high-throughput functional screens.

Genome-wide association study reveals dynamic role of genetic variation in infant and early childhood growth.

Infant and childhood growth are dynamic processes with large changes in BMI during development. By performing genome-wide association studies of BMI at 12 time points from birth to eight years (9286 children, 74,105 measurements) in the Norwegian Mother, Father, and Child Cohort Study, replicated in 5235 children, we identify a transient effect in the leptin receptor (LEPR) locus: no effect at birth, increasing effect in infancy, peaking at 6-12 months (rs2767486, P6m = 2.0 × 10-21, ß6m = 0.16 sd-BMI), and little effect after age five. We identify a similar transient effect near the leptin gene (LEP), peaking at 1.5 years (rs10487505, P1.5y = 1.3 × 10-8, ß1.5y = 0.079 sd-BMI). Both signals are protein quantitative trait loci for soluble-LEPR and LEP in plasma in adults independent from adult traits mapped to the respective genes, suggesting key roles of common variation in the leptin signaling pathway for healthy infant growth.

PathwayMatcher: proteoform-centric network construction enables fine-granularity multiomics pathway mapping.

BACKGROUND: Mapping biomedical data to functional knowledge is an essential task in bioinformatics and can be achieved by querying identifiers (e.g., gene sets) in pathway knowledge bases. However, the isoform and posttranslational modification states of proteins are lost when converting input and pathways into gene-centric lists. FINDINGS: Based on the Reactome knowledge base, we built a network of protein-protein interactions accounting for the documented isoform and modification statuses of proteins. We then implemented a command line application called PathwayMatcher (github.com/PathwayAnalysisPlatform/PathwayMatcher) to query this network. PathwayMatcher supports multiple types of omics data as input and outputs the possibly affected biochemical reactions, subnetworks, and pathways. CONCLUSIONS: PathwayMatcher enables refining the network representation of pathways by including proteoforms defined as protein isoforms with posttranslational modifications. The specificity of pathway analyses is hence adapted to different levels of granularity, and it becomes possible to distinguish interactions between different forms of the same protein.