Developmental disorders (DDs), such as autism spectrum disorder (ASD), incorporate various conditions; once identified, further diagnostics are necessary to specify their type and severity. The aim of this exploratory study was to identify genetic variants that can help differentiate ASD early from other DDs. We selected 36 children (mean age 60.1 months) with DDs using Developmental Behavioral Scales (DBS) through “EDUS-Education for All”, an organization providing services for children with DDs in Bosnia and Herzegovina. We further rated children’s autistic traits with the preschool version of the Childhood Autism Rating Scale, second edition (CARS-II). We defined ASD if scores were >25.5 and other DDs if scores were <25.5. Diagnosis of ASD and DD were independently confirmed by child psychiatrists. Whole exome sequencing (WES) was performed by Veritas Genetics, USA, using Illumina NovaSeq 6000 (Illumina Inc., San Diego, CA, USA) NGS sequencing apparatus. We tested genetic association by applying SKAT-O, which optimally combines the standard Sequence Kernel Association Test (SKAT) and burden tests to identify rare variants associated with complex traits in samples of limited power. The analysis yielded seven genes (DSE, COL10A1, DLK2, CSMD1, FAM47E, PPIA, and PYDC2) to potentially differentiate observed phenotypic characteristics between our cohort participants with ASD and other DDs. Our exploratory study in a small sample of participants with ASD and other DDs contributed to gene discovery in differentiating ASD from DDs. A replication study is needed in a larger sample to confirm our results.

Abstract This paper explores the influence of macroeconomic indicators, namely GDP growth, the Consumer Price Index and the unemployment rate on the quality of loan repayments by households in the banking market of the Federation of Bosnia and Herzegovina. Potential influence is observed over a period of fourteen years at the level of nonperforming household loans using regression analysis. The authors aim to determine whether macroeconomic forces actually influence loan repayment, and if so how and what can be done by banks to utilize this information in order to reduce future credit losses, and by the government to maintain the stability of the banking sector.

This research explores most dominant lending product to population of Bosnia and Herzegovina, a consumer loan, with aim to answer the question of what factors trigger loan repayment failure. It explores relation of borrower characteristics such as gender, age, level of indebtness to likeliness of loan repayment by use of probit on banking data sample representing 39% of the market share in the country. It identifies factors which lead to loan repayment failure and also provides exact empirical model for default prediction at loan approval stage. Main audience of this research should be banks, which could use the finding of the study to adjust their credit policies and risk appetite to ensure that lending losses from this strongly present product are minimized, thus leading to stable and financially sound banking sector.