Chronic Kidney Disease of Uncertain Etiology

Key Points

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A number of geographic regions around the world have an unexpectedly high prevalence of kidney disease among persons without previously identified risk factors for kidney disease.
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Agricultural work is the predominant occupation in three of the best-studied hotspots: Pacfic-Coast Central America, North Central and Central Province, Sri Lanka, and Uddanam region within Andhra Pradesh, India.
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Kidney biopsy series, though small in number, indicate tubulointersitial disease with variable degrees of glomeruloscelorisis across all three regions.
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Accurate assessments of prevalence and incidence are challenging, in part due to resource limitations but also due to lack of clear demographic or clinical (laboratory-based) parameters distinguishing chronic kidney disease from chronic kidney disease of unknown etiology.
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Several hypotheses regarding cause are under study, including recurrent heat stress; exposure to ground water toxin; or infection. The investigation of these hypothesized causes necessitates collaborations across occupational health, environmental epidemiology, and nephrology, in addition to a number of large international studies building scienitific resources and capacity in otherwise underresourced regions.

Since the latter part of the 20th and early 21st century, nephrologists have identified a progressive kidney disease, primarily tubulointerstitial on kidney biopsy, occurring in specific regions of South Asia and Central America, and among persons without previously identified risk factors for kidney disease. Much remains unknown and unclear about this disease, starting from nomenclature. In this chapter we use the term “Chronic Kidney Disease of Uncertain Etiology (CKDu)” but the terms Meso-American endemic Nephropathy (MeN), Uddanam Nephropathy, and Chronic interstitial nephritis in agricultural communities (CINAC) are also commonly used. “CKDu” is an inherently broad and opaque term. In this chapter, we use CKDu to refer to the highly-prevalent kidney disease in specific agricultural regions, disproportionate to the age distribution and diabetes prevalence, and in which kidney biopsies, where conducted, have demonstrated primarily tubulointerstitial kidney disease. We distinguish this entity from many other patients with “unknown” CKD, which could occur due to late presentation or lack of access to diagnostic testing, and other known causes of tubulointerstitial kidney disease such as hypersensitivity reaction to antibiotics or autoimmune disease such as sarcoidosis.

A number of other “endemic” regional nephropathies might historically have met criteria for CKDu until the cause was identified. These include unregulated release of cadmium into the Jintsu river during World War II in Japan, leading to contaminated rice paddy fields and an outbreak of “itai-itai” disease; lead nephropathy due to lead-based paint used in verandas in Queensland, Australia; and aristolochic acid nephropathy in the Balkans in the 1940s where a nephrotoxic weed growing in the wheat fields was admixing with families’ flour. Tubular injury predominated as the primary finding on biopsy in all three of these regional nephropathies. In the latter case of Balkan endemic nephropathy, although the timeline to identification of the cause was prolonged—nearly 6 decades—eventually definitive evidence emerged to identify chronic dietary exposure to aristolochic acid as the cause. Its discovery was serendipitously facilitated by a 1990s “outbreak” of rapidly progressive renal failure with tubulointerstitial nephritis among women attending a weight-loss clinic in Belgium. These women had ingested Chinese herbs, iterative analyses of which yielded the presence of aristolochic acid. Subsequent translational work identified aristolochic acid DNA adducts in affected patients’ kidney tissue or urine. Research in CKDu cause(s) is yet to identify such convincing evidence linking epidemiology to pathology and thereafter to pathophysiology, as was eventually described for Balkan endemic nephropathy.

First descriptions in three hotspot regions

From Bajo Lempa in El Salvador to Other Coastal Regions in Central America

Lacking any systematically collected end-stage kidney failure or CKD registry data, a rise in kidney disease–related hospitalizations alerted nephrologists in El Salvador to an unusual kidney disease occurring in their regions. A 1999 study in El Salvador noted that two-thirds of these patients exhibited a peculiar profile, distinguishing them from that of the classic patients with CKD: they were relatively young (mean age 51 years), mostly male (87%), agricultural workers (63%) from specific coastal regions and lacked history of diabetes or hypertension (96%). Several subsequent studies confirmed a similar profile ^, ( Fig. 83.1 ). Most patients seemed to come from the basin and the mouth of the Lempa River; hence the epidemic was referred to as the “Bajo Lempa nephropathy” in El Salvador ( Fig. 83.2 ). Simultaneous observations and subsequent studies demonstrated the presence of the disease in other geographic hotspots along the whole Pacific Ocean Mesoamerican coastline from southern Mexico to Panama, also comprising Guatemala, El Salvador, Nicaragua, and Costa Rica. ^, Many researchers and nephrologists began to group these patients together using the term “Mesoamerican endemic nephropathy (MeN) (see Chapter 74 ). ”

A two-part bar graph, labeled A and B, shows the prevalence of abnormal serum creatinine in five villages by primary occupation and age group. The horizontal axis represents different occupations as mining or subsistence farming, banana or sugarcane, fishing, services, and coffee. The vertical-axis represents the percentage of individuals with abnormal serum creatinine, ranging from 0 to 70. Each bar corresponds to an age group, with colors for 20 to 29 years, 30 to 39 years, 40 to 49 years, and 50 to 60 years. In graph A, the highest prevalence is seen in mining or subsistence farming and banana or sugarcane occupations, particularly in the 50 to 60-year-old group. The fishing sector has moderate prevalence, while the service and coffee sectors show lower values, with prevalence increasing in older age groups. Graph B, in contrast, displays significantly lower percentages across all occupations. The trend of increased prevalence with age remains visible, but the overall percentage is reduced compared to graph A. — Fig. 83.1

A two-part map, labeled left and right, shows chronic kidney disease mortality rates and maximum temperatures in El Salvador from 2011 to 2015. The left map illustrates accumulated mortality rates per 100,000 inhabitants due to chronic kidney disease by municipality. The color gradient ranges from no deaths to the highest mortality rates. The legend categorizes mortality rates into five groups: 0, 7.8 to 18.6, 18.7 to 27.1, 27.2 to 39.7, and 39.8 to 102.3 per 100,000 inhabitants. The highest mortality rates, shown in dark red, are concentrated in the southern and coastal regions. A scale bar at the bottom indicates a distance of 25 kilometers. The right map represents absolute maximum temperatures in El Salvador, with a color gradient from 24 degrees Celsius to 46 degrees Celsius. The legend provides temperature categories in increments of two degrees Celsius. The highest temperatures are primarily found in the southern and coastal regions, aligning with the areas of high mortality in the left map. — Fig. 83.2

Later studies described the clinical profile of the disease at earlier stages. Patients were described as presenting with cramps, paresthesia, muscle weakness, and occasionally with aseptic dysuria. ^, Presentation with an acute kidney injury (AKI) event has also been described, with accompanying fever and pyuria, with limited long-term follow-up data. ^, Blood pressure is normal referent to population averages, proteinuria is minimal or absent (except in advanced stages, when secondary glomerulosclerosis may be substantial), and hyperuricemia and electrolyte disturbances, especially hypokalemia and hyponatremia, are common. A family history of CKD is also common. In advanced stages, patients often present with elevated serum creatinine levels, variable proteinuria, important anemia, and uremia, but still with normal or only slightly elevated blood pressure, normal or low potassium levels, and absence of edema or even dehydration. Yet no single presenting feature is considered pathognomonic among clinicians practicing in the region, and the diagnosis is generally established by ruling out other common causes of CKD and/or pursuing kidney biopsy.

North Central and Central Province, Sri Lanka

Mirroring the story from El Salvador, in the mid-1990s, alarmingly high numbers of young farmers from rural communities in the North Central Province of Sri Lanka presented to the regional tertiary care hospital with uremic emergencies. There was no identifiable cause in the majority of these patients, who commonly presented with kidney failure requiring acute peritoneal dialysis as the only available treatment option. Comparing data from two regional hospitals, the number of hospitalizations for kidney failure due to unknown reasons was found to be highest among people residing in the North Central Province of the country. A population-based study of >6000 persons in three different geographical locations of the country reported on the prevalence of dipstick-detected proteinuria. Although the prevalence of dipstick-positivity was <10% in all three regions, in the surveyed North Central region a large proportion (87%) of those with dipstick-detected proteinuria did not have an identifiable cause, compared with a cause being identified in >90% with dipstick-detected proteinuria in the two other surveyed regions.

Early efforts relied on dipsticks, but given that the pathologic lesion of the disease is primarily tubulointerstitial, such screening efforts may have lacked sensitivity and specificity. Thereafter several waves of community screening and detection efforts have occurred in Sri Lanka, with variable success. Since a majority of the rural population relies on government-funded health care, which is integrated across primary to tertiary care, one report used hospital- and clinic-based case records to map the geographic distribution of CKD ( Fig. 83.3 ). Population-based data surveying the expected low and high prevalent regions based on this map indicate a prevalence of estimated glomerular filtration rate (eGFR) of <60 mL/min/1.73 m ² of up to 12% among men without diabetes or hypertension in the North Central Province. A biopsy study demonstrated that primary tubulointerstitial kidney disease was present in nearly half of kidney biopsies performed in the major tertiary center in the Central Province.

A map of Sri Lanka displays the geographic distribution of chronic kidney disease cases by Divisional District, based on hospital and clinic records from 2003 to 2016. The map uses a color-coded legend to indicate the number of patients per district for 1 to 50 cases, 50 to 100 cases, 100 to 500 cases, 500 to 1000 cases, and more than 1000 cases. Plain areas indicate regions with no available information. The North Central Province, particularly areas around Anuradhapura and Polonnaruwa, exhibits the highest concentration of cases, with several districts shaded in light and dark colors. An inset box lists ten districts with significant case numbers are including Medawachchiya, Kebithigollewa, Padaviya, Hambewa, Horowpothana, Kahatagaskadigiliya, Medirigiriya, Dimbulagala, Elahera, and Hingurakgoda. Major district names, including Anuradhapura and Polonnaruwa, are labeled for reference. — Fig. 83.3

Some clear similarities exist in the demographic and clinical characteristics of Sri Lankan and Central American patients: a male predominance among those affected, reports of significant hypokalemia in the early stages, and a subset may present acutely with systemic illness. ^, Notable differences include a biochemical profile with hypernatremia and lack of significant hyperuricemia in Sri Lanka compared with Central America. ^, Table 83.1 summarizes some similarities and differences in clinical presentation and associated features on the basis of existing data from the two best-described hotspots.

Table 83.1

Similarities and Differences in Clinical Presentation and Other Associated Features of Chronic Kidney Disease of Unknown Etiology in the 2 Best-Described Hotspots

	Mesoamerica	Sri Lanka
Geospatial Factors
Hot, dry climate	✓	✓
Reliance on groundwater supply	✓	✓
High-density agrochemical application	✓	✓
Low population–based prevalence of diabetes	✓	✘
Clinical Presentation/Other Associated Features
Male predominance	✓	✓
Lack of heavy proteinuria	✓	✓
Significant hyperuricemia	✓	✘
Significant hypokalemia	✓	?
Extensive use of NSAIDs	✓	✘
Specific job tasks with higher risk	✓	✘
Common tobacco use	?	✓
Biopsy Data
Chronic tubulointerstitial nephritis and fibrosis	✓	✓
Some with primarily acute interstitial nephritis	✓	✓
No immune complex deposition	✓	✓
Significant glomerulosclerosis	✓	?

Question mark symbols indicate lack of definitive data to make a determination.

NSAIDs, Nonsteroidal antiinflammatory drugs.

There is an interesting historical context to CKDu-endemic regions in Sri Lanka. Before 1970s, the CKDu-endemic areas in Sri Lanka were sparsely populated. Several major irrigational projects were launched to divert water from the wet zonal hill country to the north central and central dry zones for enhancing agriculture to ensure food security of the country. In parallel, there was intentional large-scale population migration from wet zonal areas to these dry zonal areas of the country. The CKDu epidemic emerged approximately 2 decades later. This historical timeline has heightened suspicions of environmental exposure, specifically water-based exposure, as a potential contributor to the epidemic.

Uddanam Region, India

Another major recognized hotspot of CKDu is in southern India, termed “Uddanam endemic nephropathy” for the specific region within Andhra Pradesh, where an endemic kidney disease was first recognized. Uddanam is a coastal region of this state, also relying primarily on agriculture but with a greater variety of crops including coconut, cashews, rice paddy, and vegetable cultivation ( Fig. 83.4 ) (see Chapter 77 ).

A three-part map, labeled A, B, and C, shows the Uddanam region in Andhra Pradesh, India, highlighting study areas, sample villages, and village distribution. The Map A shows the administrative boundaries of India, with Andhra Pradesh highlighted in yellow. The legend identifies boundaries and study areas. A scale bar at the bottom indicates distances ranging from 0 to 1,900 kilometers. Map B zooms into Andhra Pradesh, marking the Srikakulam district. The legend differentiates sample villages, the study area in Uddanam, the control area, and district boundaries. A scale bar at the bottom represents distances from 0 to 440 kilometers. Map C presents a satellite view of the villages in Uddanam, Srikakulam, along the Bay of Bengal. The study area boundary is outlined in color. Color dots mark village locations, and numbers label individual villages. Named towns include Ichchapuram, Kanchili, Kaviti, Sompeta, Mandasa, Palasa, and V. Kothuru. A scale bar at the bottom represents distances from 0 to 22 kilometers. A north arrow is present in each map for orientation. — Fig. 83.4

A large cross-sectional study of more than 2400 persons from this region indicated nearly 20% of men and 16% of women had CKD, a majority (>70%) were engaged in farm work, diabetes was present in less than 20%, and family history of kidney disease was reported in 25% of the subset with eGFR <60 mL/min/1.73 m ². A prior study had reported similar findings. Notably, in the earlier study of 2200 persons, nearly 50% of persons with CKD had urine-to-protein creatinine ratios <0.2 g/g. A small case series confirmed that the primary findings among five men and one woman on biopsy were predominant tubulointerstitial lesions with a variable degree of glomerulosclerosis, with serum creatinine levels <2 mg/dL in the majority.

In a recent follow-up study using verbal autopsies in the region, CKD was identified as the primary cause of death among 133 deaths, accounting for 45% of all deaths in the region. For context, in the Million Death Study, conducted across all of India, CKD was determined to be the cause of 2.9% of the deaths among persons 15 to 69 years of age.

Challenges to Detection Efforts

Despite substantial coverage in the popular media, robust data on the burden of CKDu globally remain sparse outside of a few intensely studied regions in Central America and South Asia. In part, this reflects the challenges of capturing estimates of disease in the populations affected, which are typically served by poorly developed health systems and which have inadequate access to care (including kidney replacement therapy). This means routine health record data sources, such as death certificates or dialysis registries, can only provide limited insights into the disease burden and risk factors in most regions.

Efforts to characterize the prevalence of CKDu using population-representative surveys are ongoing. ^, These studies are resource intensive as eGFR testing based on blood sampling is required to define cases, given that urinary abnormalities are not typical in CKDu. eGFR test values can in turn be challenging to interpret as alongside interlaboratory variability, neither eGFR estimating equations nor the healthy population distribution of the measured GFR are generalizable across regions. The epidemiologic study designs used typically include only a single measure of eGFR without confirmation of chronicity, which may overestimate CKD prevalence. These studies also have limitations surrounding (often variable) case definitions for CKDu. Differentiating cases of CKDu from other causes of CKD is challenging even at the individual level, and pragmatic definitions such as the absence of significant proteinuria, hypertension, and diabetes (and sometimes retroviral disease and nephrotoxic drug use) are necessary in epidemiologic studies. These factors all inevitably lead to misclassification because 1. not all CKD is CKDu even in endemic areas; 2. both diabetes and hypertension, although not features of the disease, can clearly coexist with CKDu; and 3. there are cases of nonproteinuric CKD (e.g., due to drugs and genetic disorders or of unclear etiology) in all regions (i.e., including high-income nonagricultural settings), although this constellation likely does not represent the same clinical entity as the “CKDu” disease(s) described in this chapter. Nonetheless, assuming the contribution of any misclassification is low, as will be the case where there are high levels of CKDu, these studies can still provide valuable insight into the burden of, and risk factors for, CKDu across different regions globally. A number of population-representative studies conducted in areas of reported high CKDu burden, or with the specific aim of studying CKDu prevalence, are summarized in Table 83.2 .

Table 83.2

Summary of Chronic Kidney Disease of Unknown Etiology Detection Efforts in Cross-Sectional Population-Based Studies

Reference	Year Published	Sub-Continent	Country and Region	N	Exclusion of Diabetes	Exclusion of Hypertension (Threshold)	Exclusion of Proteinuria (Threshold)	Other Exclusions	Chronicity Demonstrated	% eGFR <60 mL/min/1.73 m ²	Independent Risk Factors for CKD/CKDu as defined by eGFR <60 mL/min/1.73 m ²
O’Donnell et al.	2011	Central America	Leon, Nicaragua	771	N but low prevalence	N	N		N	13%	Age Male sex Low altitude
Torres et al.	2010	Central America	Leon and Chinandega, Nicaragua	1096	N but low prevalence	N	N		N	8.7%	Age Male sex Agricultural or mining communities
Peraza et al. https://doi.org/10.1053/j.ajkd.2011.11.039	2012	Central America	Pacific Coast, El-Salvador	664	N but low prevalence	N	N		N	0% in high altitude/urban areas 10% in sugarcane communities	Age Male sex Low Altitude Sugarcane/cotton work Tobacco use (males only) Kidney stones (males only) Diabetes (females only) Hypertension (females only)
Orantes et al.	2011	Central America	Bajo Lempa, El-Salvador	775	Y	Y	N		Y	3.6%	Age Male sex Family history of CKD
Miller et al. https://doi.org/10.1016/j.ekir.2020.12.015	2021	Central America	Tecpán, Guatemala and San Antonio Suchitepéquez, Guatemala	807	N	N	N		N (Sensitivity analysis only)	4.0%	Age Diabetes Hypertension Low BMI Sugarcane work in poorer participants
Ruiz-Alejos et al.	2021	South America	Tumbes, Peru	1,514	Y	Y (140/90)	Y		N	0.9%	Numbers too small to undertake adjusted analyses in those without hypertension or diabetes
O’Callaghan-Gordo et al.	2019	South Asia	Chennai, Visakhapatnam, Haryana and Delhi, India	12,500 (after exclusion of diabetes and hypertension)	Y	Y (140/90)	Y		N	1.4% Urban Northern areas 1.9% Rural Northern areas 0.43% Urban Southern area 4.8% Rural Southern area	Age Rural residence (Southern areas only) Fewer years of education
Tatapudi et al.	2019	South Asia	Uddanam, India	2210	Y	Y (140/90 for more than 5 years)	Y (PCR >1000 mg/g)		N	13.3%	Age
Gummidi et al.	2020	South Asia	Uddanam, India	2419	N	N	N		Y	10.2%	Age Male sex Hypertension Tobacco use Lack of formal education Outdoor work Family history of CKD Analgesic use
Ruwanpathirana et al.	2019	South Asia	Anuradhapura district, Sri Lanka	4803	Y	Y (140/90)	Y (ACR >300 mg/g)			3.7% in lowest impacted area 8.5% in highest impacted area	Age Male sex Family history of CKD Tobacco use (males only)
Jayatilake et al.	2013	South Asia	Anuradhapura, Badulla, Hambantota and Polonnaruwa districts, Sri Lanka	4957	Y	Y (160/90)	N		N	NA Proteinuria screening only
Hathaway et al.	2023	Sub-Saharan Africa	Kisumu, Kenya	782	Y	Y	Y	HIV	N	0%	NA
Hamilton et al.	2020	Sub-Saharan Africa	Lilongwe and Karonga district Malawi	821	Y	Y (140/90)	Y			0.2%	NA
Aekplakorn et al.	2023	Southeast Asia	National, Thailand	17,329	Y	Y (140/90)	Y (urinalysis >1+)	Age>70	N	0.7% Central, South and Bangkok regions 1.6% Northeast region	Age Female sex Gout Kidney stones Rural residence Analgesic use Manual labour/agricultural work Low BMI

Due to the differences in population age structures and the other limitations described earlier, the results of the above studies are not directly comparable, although a number of common themes can be identified.

Firstly, where CKDu epidemics are reported, population rates of eGFR <60 mL/min are typically ≥5% when those with diabetes, hypertension, and proteinuria are excluded and chronicity is not confirmed. Estimates would be expected to be 1% to 2% or lower using the same criteria (assuming similarly young populations) in non-CKDu–endemic regions.

Second, a number of risk factors are common across these studies. These include age (which is a risk factor for all forms of CKD), male sex, lower altitude, tobacco smoking, and lower levels of education/higher levels of poverty. Finally, agricultural (specifically sugarcane) work, rural residence, or residence in an agricultural community are also typically identified as risk factors, although distinguishing the occupational from residence-related risk factors is not always possible in many of these studies.

Biopsy findings

As with previous endemic nephropathies, kidney biopsy studies in these current CKDu-endemic regions are limited but consistent with a tubulointerstitial disease, showing mainly tubular atrophy with interstitial fibrosis and glomerulosclerosis related to ischemia, without immune complexes ^, ( Fig. 83.5 ). One of the first case series describing pathology findings reported data from eight men with serum creatinine ranging from 1.1 to 2.7 mg/dL, and this case series described both significant interstitial fibrosis and glomerulosclerosis. In fact, tubulitis and interstitial inflammation, although described, were not severe. However, studies from both Sri Lanka and Nicaragua recruited patients with “acute symptoms” (e.g., dysuria, fever, and AKD) from CKDu-endemic regions and showed features of acute interstitial nephritis (i.e., tubulitis and inflammatory infiltrate in the tubules ^, ^, ^, ), with changes in the glomeruli confined to areas with chronic interstitial damage. Assuming this clinical presentation represents the onset of CKDu, these studies would favor the argument that a primary tubulointerstitial disease leads to secondary glomerulosclerosis but certainly do not rule out the possibility that an ischemic insult is driving both tubulointerstitial and glomerular injury in parallel.

Deeper review of tissue samples has brought a finding of potential interest: electron-dense lysosomal granules in the tubules. ^, The authors hypothesized that these granules may indicate an injury pathway similar to that instigated by calcineurin inhibition. Of note, however, is that replication studies have demonstrated these findings to be relatively nonspecific as others were able to identify similar granules in persons with known glomerular disease. Additional electron microscopic findings described include patchy podocyte foot process effacement, tubular vacuolization, and mitochondrial swelling.

Several challenges exist in describing the spectrum of kidney pathology observed with CKDu. A small sample of persons with CKDu undergoes biopsy, with quantitatively fewer biopsies available from Central America than from Sri Lanka. In Central America, patient-borne costs are higher. Lack of dedicated pathologists may present a further impediment. Even in persons with biopsies, there is tremendous heterogeneity in the level of kidney dysfunction at the time of biopsy. Thus in the existing literature, we lack sufficient numbers of cases to confidently match level of kidney dysfunction to tissue findings.

Developing molecular interrogation techniques holds promise for identification of pathognomic injury pathways (which could in turn provide clues to potential etiologies). However, application of these techniques (e.g., single-cell RNA sequencing) requires resource-intensive tissue handling and storage, further complicated by the need to transfer tissue from regional hotspots to the specialized centers with technical expertise.

Hypothesized Cause(s) of CKDu

Despite intensive efforts for more than 2 decades, some of which have garnered well-deserved attention by the lay press, as of this chapter’s writing no specific etiology is widely accepted as the primary driver of disease. The hypothesized causes span multiple domains including genetic, infectious, occupational, and environmental ( Fig. 83.6 ). The prolonged struggle to eliminate or deprioritize any of these broad domains reflects, among other factors, the failure to identify early kidney disease, matched with lack of methodologies to elicit cumulative (lifetime) measures of exposures ( Fig. 83.7 ). This in turn complicates prospective investigations which need to continue to expend resources to interrogate multiple domains.