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Predictive model of declining glomerular filtration rate in type 2 diabetes mellitus with poorly glycemic control: Integration of RAAS and TGFB polymorphisms with clinical risk factors in the Jambi Malay population

Proceedings Academic Universitas Jambi · Vol. 1 No. 2 (2025) · pp. 535–544

DOI
10.22437/proca.v1i2.50317
Published
2025-11-29
Publisher
LPPM Universitas Jambi
Language
en
License
creativecommons.org/licenses/by/4.0

Abstract

Background: Diabetic kidney disease (DKD) is a major complication of type 2 diabetes mellitus (T2DM) and a leading cause of end-stage renal disease worldwide. Despite optimal glycemic and blood pressure control, many patients experience renal decline, suggesting a role for genetic factors. Objective: To develop a predictive model integrating clinical and genetic parameters to identify individuals at risk of declining glomerular filtration rate (GFR) among Malay Jambi patients with poorly controlled T2DM. Methods: A cross-sectional study of 62 patients was conducted using ACE rs4343 and TGFB1 rs1800470 genotyping by Tetra-ARMS PCR. Declining renal function was defined as eGFR <60 mL/min/1.73 m² (KDIGO 2024). Logistic regression and ROC analyses assessed model performance. Results: Older age and higher blood pressure were associated with reduced GFR. The TGFB1 rs1800470 TT and ACE rs4343 AG genotypes significantly increased the risk of renal decline (adjusted OR 7.79 and 5.98, respectively; p < 0.05). The integrated clinical–genetic model achieved the highest discrimination (AUC = 0.859; sensitivity 78.9%; specificity 88.4%). Conclusion: Integrating ACE and TGFB1 genotypes with clinical factors enhances DKD risk prediction and supports early genotype-informed interventions. This approach strengthens population-specific precision nephrology in Indonesia and provides a foundation for future polygenic risk model development.

Keywords

Collaboration network of the authors

40 authors · 236 co-authorship links · showing the 40 most connected

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  • Universitas Jambi
  • Affiliation unknown
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  • Same organisation
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Co-authorOrganisationJoint articles
Rina Nofri EnisAffiliation unknown54
Wahyu Indah Dewi AuroraAffiliation unknown42
Herlambang HerlambangUniversitas Jambi35
Susan TarawifaAffiliation unknown25
Armaidi DarmawanAffiliation unknown24
Rita HalimAffiliation unknown19
Tengku Arief Buana PerkasaAffiliation unknown16
Huntari HarahapAffiliation unknown12
Ima MariaAffiliation unknown11
Nuriyah NuriyahAffiliation unknown10
ELFIANI ELFIANIAffiliation unknown9
HerlambangAffiliation unknown8
Asro Hayani HarahapAffiliation unknown7
Afifah AmatullahAffiliation unknown6
Tia Wida EkaputriAffiliation unknown6
Andika SulistiawanAffiliation unknown5
Raihanah SuzanAffiliation unknown4
AuroraAffiliation unknown4
Mirna Marhami IskandarAffiliation unknown4
Anati PurwakanthiAffiliation unknown4
NuriyahAffiliation unknown3
Diana Nur AfifahAffiliation unknown3
Gemala AnjaniAffiliation unknown3
Irawan Anasta PutraAffiliation unknown3
Nadir Putra Indra TariganAffiliation unknown3
Ratna SugiartiAffiliation unknown3
Patrick Wiliam GadingAffiliation unknown3
Budi JustisiaAffiliation unknown3
Fairuz FairuzAffiliation unknown3
Siti RaudhohAffiliation unknown3
Nindya AryantyAffiliation unknown3
Mara Imam Taufiq SiregarAffiliation unknown2
Hasna DewiAffiliation unknown2

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://online-journal.unja.ac.id/index.php/PROCA/oai, first harvested 6 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Predictive model of declining glomerular filtration rate in type 2 diabetes mellitus with poorly glycemic control: Integration of RAAS and TGFB polymorphisms with clinical risk factors in the Jambi Malay population</dc:title>
	<dc:creator xml:lang="en">Puspasari, Anggelia</dc:creator>
	<dc:creator xml:lang="en">Elfiani</dc:creator>
	<dc:creator xml:lang="en">Maharani, Citra</dc:creator>
	<dc:creator xml:lang="en">Syauqy, Ahmad</dc:creator>
	<dc:creator xml:lang="en">Kusdiyah, Erny</dc:creator>
	<dc:creator xml:lang="en">Shafira, Nyimas Natasha Ayu</dc:creator>
	<dc:creator xml:lang="en">Fitri, Amelia Dwi</dc:creator>
	<dc:subject xml:lang="en">Type 2 diabetes mellitus; diabetic kidney diseases; declining GFR; RAAS; TGFB; genetic polymorphism; poorly glycemic control; Malay population</dc:subject>
	<dc:description xml:lang="en">Background: Diabetic kidney disease (DKD) is a major complication of type 2 diabetes mellitus (T2DM) and a leading cause of end-stage renal disease worldwide. Despite optimal glycemic and blood pressure control, many patients experience renal decline, suggesting a role for genetic factors. Objective: To develop a predictive model integrating clinical and genetic parameters to identify individuals at risk of declining glomerular filtration rate (GFR) among Malay Jambi patients with poorly controlled T2DM. Methods: A cross-sectional study of 62 patients was conducted using ACE rs4343 and TGFB1 rs1800470 genotyping by Tetra-ARMS PCR. Declining renal function was defined as eGFR &amp;lt;60 mL/min/1.73 m² (KDIGO 2024). Logistic regression and ROC analyses assessed model performance. Results: Older age and higher blood pressure were associated with reduced GFR. The TGFB1 rs1800470 TT and ACE rs4343 AG genotypes significantly increased the risk of renal decline (adjusted OR 7.79 and 5.98, respectively; p &amp;lt; 0.05). The integrated clinical–genetic model achieved the highest discrimination (AUC = 0.859; sensitivity 78.9%; specificity 88.4%). Conclusion: Integrating ACE and TGFB1 genotypes with clinical factors enhances DKD risk prediction and supports early genotype-informed interventions. This approach strengthens population-specific precision nephrology in Indonesia and provides a foundation for future polygenic risk model development.</dc:description>
	<dc:publisher xml:lang="en">LPPM Universitas Jambi</dc:publisher>
	<dc:date>2025-11-29</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://online-journal.unja.ac.id/PROCA/article/view/50317</dc:identifier>
	<dc:identifier>10.22437/proca.v1i2.50317</dc:identifier>
	<dc:source xml:lang="en">Proceedings Academic Universitas Jambi; Vol. 1 No. 2 (2025): The 6th Jambi Medicine and Health Science International Conference (JAMHESIC); 535-544</dc:source>
	<dc:source>10.22437/proca.v1i2</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://online-journal.unja.ac.id/PROCA/article/view/50317/22637</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2025 Anggelia Puspasari, Elfiani, Citra Maharani, Ahmad Syauqy, Erny Kusdiyah, Nyimas Natasha Ayu Shafira, Amelia Dwi Fitri</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0</dc:rights>
</oai_dc:dc>