Targeted Exome Sequencing of Genes Involved in Rare CNVs in Early-Onset Severe Obesity Article Swipe
Petra Loid
,
Minna Pekkinen
,
Taina Mustila
,
Päivi Tossavainen
,
Heli Viljakainen
,
Anna Lindstrand
,
Outi Mäkitie
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3389/fgene.2022.839349
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3389/fgene.2022.839349
Context: Rare copy number variants (CNVs) have been associated with the development of severe obesity. However, the potential disease-causing contribution of individual genes within the region of CNVs is often not known. Objective: Screening of rare variants in genes involved in CNVs in Finnish patients with severe early-onset obesity to find candidate genes linked to severe obesity. Methods: Custom-made targeted exome sequencing panel to search for rare (minor allele frequency <0.1%) variants in genes affected by previously identified CNVs in 92 subjects (median age 14 years) with early-onset severe obesity (median body mass index (BMI) Z-score + 4.0). Results: We identified thirteen rare heterozygous variants of unknown significance in eleven subjects in twelve of the CNV genes. Two rare missense variants (p.Pro405Arg and p.Tyr232Cys) were found in SORCS1 , a gene highly expressed in the brain and previously linked to diabetes risk. Four rare variants were in genes in the proximal 16p11.2 region (a frameshift variant in TAOK2 and missense variants in SEZ6L2 , ALDOA and KIF22 ) and three rare missense variants were in genes in the 22q11.21 region ( AIFM3, ARVCF and KLHL22 ). Conclusion: We report several rare variants in CNV genes in subjects with childhood obesity. However, the role of the individual genes in the previously identified rare CNVs to development of obesity remains uncertain. More studies are needed to understand the potential role of the specific genes within obesity associated CNVs.
Related Topics
Concepts
Copy-number variation
Exome sequencing
Genetics
Missense mutation
Biology
Exome
Gene
Frameshift mutation
Candidate gene
Minor allele frequency
Allele
Context (archaeology)
Allele frequency
Mutation
Genome
Paleontology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/fgene.2022.839349
- https://www.frontiersin.org/articles/10.3389/fgene.2022.839349/pdf
- OA Status
- gold
- Cited By
- 6
- References
- 38
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4221016942
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4221016942Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3389/fgene.2022.839349Digital Object Identifier
- Title
-
Targeted Exome Sequencing of Genes Involved in Rare CNVs in Early-Onset Severe ObesityWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-03-07Full publication date if available
- Authors
-
Petra Loid, Minna Pekkinen, Taina Mustila, Päivi Tossavainen, Heli Viljakainen, Anna Lindstrand, Outi MäkitieList of authors in order
- Landing page
-
https://doi.org/10.3389/fgene.2022.839349Publisher landing page
- PDF URL
-
https://www.frontiersin.org/articles/10.3389/fgene.2022.839349/pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.frontiersin.org/articles/10.3389/fgene.2022.839349/pdfDirect OA link when available
- Concepts
-
Copy-number variation, Exome sequencing, Genetics, Missense mutation, Biology, Exome, Gene, Frameshift mutation, Candidate gene, Minor allele frequency, Allele, Context (archaeology), Allele frequency, Mutation, Genome, PaleontologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
6Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2024: 2, 2023: 1, 2022: 1Per-year citation counts (last 5 years)
- References (count)
-
38Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.CNVs | 27, 41, 78, 212 |
| abstract_inverted_index.Four | 142 |
| abstract_inverted_index.More | 219 |
| abstract_inverted_index.Rare | 1 |
| abstract_inverted_index.been | 7 |
| abstract_inverted_index.body | 91 |
| abstract_inverted_index.copy | 2 |
| abstract_inverted_index.find | 50 |
| abstract_inverted_index.gene | 130 |
| abstract_inverted_index.have | 6 |
| abstract_inverted_index.mass | 92 |
| abstract_inverted_index.rare | 35, 66, 102, 118, 143, 170, 190, 211 |
| abstract_inverted_index.role | 202, 227 |
| abstract_inverted_index.were | 124, 145, 173 |
| abstract_inverted_index.with | 9, 45, 86, 197 |
| abstract_inverted_index.(BMI) | 94 |
| abstract_inverted_index.4.0). | 97 |
| abstract_inverted_index.ALDOA | 164 |
| abstract_inverted_index.ARVCF | 182 |
| abstract_inverted_index.CNVs. | 235 |
| abstract_inverted_index.KIF22 | 166 |
| abstract_inverted_index.TAOK2 | 157 |
| abstract_inverted_index.brain | 135 |
| abstract_inverted_index.exome | 60 |
| abstract_inverted_index.found | 125 |
| abstract_inverted_index.genes | 22, 38, 52, 73, 147, 175, 194, 206, 231 |
| abstract_inverted_index.index | 93 |
| abstract_inverted_index.often | 29 |
| abstract_inverted_index.panel | 62 |
| abstract_inverted_index.risk. | 141 |
| abstract_inverted_index.three | 169 |
| abstract_inverted_index.(CNVs) | 5 |
| abstract_inverted_index.(minor | 67 |
| abstract_inverted_index.AIFM3, | 181 |
| abstract_inverted_index.KLHL22 | 184 |
| abstract_inverted_index.SEZ6L2 | 162 |
| abstract_inverted_index.SORCS1 | 127 |
| abstract_inverted_index.allele | 68 |
| abstract_inverted_index.eleven | 109 |
| abstract_inverted_index.genes. | 116 |
| abstract_inverted_index.highly | 131 |
| abstract_inverted_index.known. | 31 |
| abstract_inverted_index.linked | 53, 138 |
| abstract_inverted_index.needed | 222 |
| abstract_inverted_index.number | 3 |
| abstract_inverted_index.region | 25, 152, 179 |
| abstract_inverted_index.report | 188 |
| abstract_inverted_index.search | 64 |
| abstract_inverted_index.severe | 13, 46, 55, 88 |
| abstract_inverted_index.twelve | 112 |
| abstract_inverted_index.within | 23, 232 |
| abstract_inverted_index.years) | 85 |
| abstract_inverted_index.(median | 82, 90 |
| abstract_inverted_index.16p11.2 | 151 |
| abstract_inverted_index.Finnish | 43 |
| abstract_inverted_index.Z-score | 95 |
| abstract_inverted_index.obesity | 48, 89, 216, 233 |
| abstract_inverted_index.remains | 217 |
| abstract_inverted_index.several | 189 |
| abstract_inverted_index.studies | 220 |
| abstract_inverted_index.unknown | 106 |
| abstract_inverted_index.variant | 155 |
| abstract_inverted_index.22q11.21 | 178 |
| abstract_inverted_index.Context: | 0 |
| abstract_inverted_index.However, | 15, 200 |
| abstract_inverted_index.Methods: | 57 |
| abstract_inverted_index.Results: | 98 |
| abstract_inverted_index.affected | 74 |
| abstract_inverted_index.diabetes | 140 |
| abstract_inverted_index.involved | 39 |
| abstract_inverted_index.missense | 119, 159, 171 |
| abstract_inverted_index.obesity. | 14, 56, 199 |
| abstract_inverted_index.patients | 44 |
| abstract_inverted_index.proximal | 150 |
| abstract_inverted_index.specific | 230 |
| abstract_inverted_index.subjects | 81, 110, 196 |
| abstract_inverted_index.targeted | 59 |
| abstract_inverted_index.thirteen | 101 |
| abstract_inverted_index.variants | 4, 36, 71, 104, 120, 144, 160, 172, 191 |
| abstract_inverted_index.Screening | 33 |
| abstract_inverted_index.candidate | 51 |
| abstract_inverted_index.childhood | 198 |
| abstract_inverted_index.expressed | 132 |
| abstract_inverted_index.frequency | 69 |
| abstract_inverted_index.potential | 17, 226 |
| abstract_inverted_index.Objective: | 32 |
| abstract_inverted_index.associated | 8, 234 |
| abstract_inverted_index.frameshift | 154 |
| abstract_inverted_index.identified | 77, 100, 210 |
| abstract_inverted_index.individual | 21, 205 |
| abstract_inverted_index.previously | 76, 137, 209 |
| abstract_inverted_index.sequencing | 61 |
| abstract_inverted_index.uncertain. | 218 |
| abstract_inverted_index.understand | 224 |
| abstract_inverted_index.Conclusion: | 186 |
| abstract_inverted_index.Custom-made | 58 |
| abstract_inverted_index.development | 11, 214 |
| abstract_inverted_index.early-onset | 47, 87 |
| abstract_inverted_index.(p.Pro405Arg | 121 |
| abstract_inverted_index.contribution | 19 |
| abstract_inverted_index.heterozygous | 103 |
| abstract_inverted_index.p.Tyr232Cys) | 123 |
| abstract_inverted_index.significance | 107 |
| abstract_inverted_index.&lt;0.1%) | 70 |
| abstract_inverted_index.disease-causing | 18 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5075609535 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 7 |
| corresponding_institution_ids | https://openalex.org/I133731052, https://openalex.org/I2800394112, https://openalex.org/I4210165462 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.8100000023841858 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.79164096 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |