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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

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Targeted massively parallel sequencing for congenital generalized lipodystrophy.

Aline D Costa-Riquetto¹, Lucas S Santana¹, Lílian A Caetano¹

¹Grupo de Diabetes Monogênico, Unidade de Endocrinologia Genética/Laboratório de Investigação Médica (LIM/25) e Unidade de Diabetes, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brasil.

Archives of Endocrinology and Metabolism

|May 25, 2021

Summary

Massively parallel sequencing (MPS), also known as next-generation sequencing (NGS), accurately diagnosed congenital generalized lipodystrophy (CGL) in nine patients. This advanced genetic testing identified pathogenic variants and deletions missed by traditional methods, highlighting its value for complex genetic disorders.

Keywords:

Berardinelli-Seip syndrome Congenital generalized lipodystrophy deep sequencing massively parallel sequencing

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Area of Science:

Genetics
Molecular Biology
Medical Diagnostics

Background:

Congenital generalized lipodystrophy (CGL) is a rare genetic disorder characterized by a near-complete absence of adipose tissue.
Accurate genetic diagnosis is crucial for understanding CGL pathophysiology and guiding patient management.
Traditional sequencing methods may not detect all types of genetic variants, such as large deletions.

Purpose of the Study:

To establish the utility of targeted massively parallel sequencing (MPS) for the genetic diagnosis of congenital generalized lipodystrophy (CGL).
To evaluate the capability of MPS in identifying diverse genetic variants, including deletions, in CGL patients.

Main Methods:

Recruitment of nine unrelated individuals with a clinical diagnosis of CGL.
Utilized a customized gene panel for targeted sequencing of known lipodystrophy-related genes.
Performed DNA library preparation, sequencing on the Illumina MiSeq platform, and subsequent bioinformatics analysis.

Main Results:

Achieved accurate genetic diagnosis for all nine CGL patients.
Identified pathogenic variants in the AGPAT2 gene in four patients and in the BSCL2 gene in three patients.
Detected three large homozygous deletions in the AGPAT2 gene through copy-number variant analysis.

Conclusions:

Targeted MPS effectively diagnosed CGL in all recruited patients.
MPS identified pathogenic variants and large deletions in CGL-associated genes, including AGPAT2 and BSCL2.
MPS is a valuable diagnostic tool for CGL and other multi-gene related genetic disorders, offering advantages over Sanger sequencing for variant detection.